Category Archives: Neurotechnology

Overview for Facial Recognition Market Helps in providing scope and definitions, Key Findings, Growth Drivers, and Various Dynamics.

Facial Recognition Market Data and Acquisition Research Study with Trends and Opportunities 2019-2024The study of Facial Recognition market is a compilation of the market of Facial Recognition broken down into its entirety on the basis of types, application, trends and opportunities, mergers and acquisitions, drivers and restraints, and a global outreach. The detailed study also offers a board interpretation of the Facial Recognition industry from a variety of data points that are collected through reputable and verified sources. Furthermore, the study sheds a lights on a market interpretations on a global scale which is further distributed through distribution channels, generated incomes sources and a marginalized market space where most trade occurs.

Along with a generalized market study, the report also consists of the risks that are often neglected when it comes to the Facial Recognition industry in a comprehensive manner. The study is also divided in an analytical space where the forecast is predicted through a primary and secondary research methodologies along with an in-house model.

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Key players in the global Facial Recognition market covered in Chapter 12:NvisoImagus Technology3M CompanyNECNeurotechnologyAyonixGemaltoFulcrum BiometricsKeylemonGoogleNetatmoSafranTechno BrainDaonLuxandAnimetricsAwareAurora Computer ServicesArcSoftHerta SecurityLathem TimeIdemiaFaceFirstCognitec SystemsXID Technologies

In Chapter 4 and 14.1, on the basis of types, the Facial Recognition market from 2015 to 2025 is primarily split into:2D Facial Recognition3D Facial RecognitionThermal Face Recognition

In Chapter 5 and 14.2, on the basis of applications, the Facial Recognition market from 2015 to 2025 covers:Emotion RecognitionAttendance Tracking and MonitoringAccess ControlLaw EnforcementOthers

Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historic and forecast (2015-2025) of the following regions are covered in Chapter 6, 7, 8, 9, 10, 11, 14:North America (Covered in Chapter 7 and 14)United StatesCanadaMexicoEurope (Covered in Chapter 8 and 14)GermanyUKFranceItalySpainRussiaOthersAsia-Pacific (Covered in Chapter 9 and 14)ChinaJapanSouth KoreaAustraliaIndiaSoutheast AsiaOthersMiddle East and Africa (Covered in Chapter 10 and 14)Saudi ArabiaUAEEgyptNigeriaSouth AfricaOthersSouth America (Covered in Chapter 11 and 14)BrazilArgentinaColumbiaChileOthersRegional scope can be customized

For a global outreach, the Facial Recognition study also classifies the market into a global distribution where key market demographics are established based on the majority of the market share. The following markets that are often considered for establishing a global outreach are North America, Europe, Asia, and the Rest of the World. Depending on the study, the following markets are often interchanged, added, or excluded as certain markets only adhere to certain products and needs.

Here is a short glance at what the study actually encompasses:Study includes strategic developments, latest product launches, regional growth markers and mergers & acquisitionsRevenue, cost price, capacity & utilizations, import/export rates and market shareForecast predictions are generated from analytical data sources and calculated through a series of in-house processes.

However, based on requirements, this report could be customized for specific regions and countries.

Brief about Facial Recognition Market Report with [emailprotected]https://hongchunresearch.com/report/facial-recognition-market-size-2020-120283

Some Point of Table of Content:

Chapter One: Facial Recognition Introduction and Market Overview

Chapter Two: Executive Summary

Chapter Three: Industry Chain Analysis

Chapter Four: Global Facial Recognition Market, by Type

Chapter Five: Facial Recognition Market, by Application

Chapter Six: Global Facial Recognition Market Analysis by Regions

Chapter Seven: North America Facial Recognition Market Analysis by Countries

Chapter Eight: Europe Facial Recognition Market Analysis by Countries

Chapter Nine: Asia Pacific Facial Recognition Market Analysis by Countries

Chapter Ten: Middle East and Africa Facial Recognition Market Analysis by Countries

Chapter Eleven: South America Facial Recognition Market Analysis by Countries

Chapter Twelve: Competitive Landscape 12.1 Nviso 12.1.1 Nviso Basic Information 12.1.2 Facial Recognition Product Introduction 12.1.3 Nviso Production, Value, Price, Gross Margin 2015-2020 12.2 Imagus Technology 12.2.1 Imagus Technology Basic Information 12.2.2 Facial Recognition Product Introduction 12.2.3 Imagus Technology Production, Value, Price, Gross Margin 2015-2020 12.3 3M Company 12.3.1 3M Company Basic Information 12.3.2 Facial Recognition Product Introduction 12.3.3 3M Company Production, Value, Price, Gross Margin 2015-2020 12.4 NEC 12.4.1 NEC Basic Information 12.4.2 Facial Recognition Product Introduction 12.4.3 NEC Production, Value, Price, Gross Margin 2015-2020 12.5 Neurotechnology 12.5.1 Neurotechnology Basic Information 12.5.2 Facial Recognition Product Introduction 12.5.3 Neurotechnology Production, Value, Price, Gross Margin 2015-2020 12.6 Ayonix 12.6.1 Ayonix Basic Information 12.6.2 Facial Recognition Product Introduction 12.6.3 Ayonix Production, Value, Price, Gross Margin 2015-2020 12.7 Gemalto 12.7.1 Gemalto Basic Information 12.7.2 Facial Recognition Product Introduction 12.7.3 Gemalto Production, Value, Price, Gross Margin 2015-2020 12.8 Fulcrum Biometrics 12.8.1 Fulcrum Biometrics Basic Information 12.8.2 Facial Recognition Product Introduction 12.8.3 Fulcrum Biometrics Production, Value, Price, Gross Margin 2015-2020 12.9 Keylemon 12.9.1 Keylemon Basic Information 12.9.2 Facial Recognition Product Introduction 12.9.3 Keylemon Production, Value, Price, Gross Margin 2015-2020 12.10 Google 12.10.1 Google Basic Information 12.10.2 Facial Recognition Product Introduction 12.10.3 Google Production, Value, Price, Gross Margin 2015-2020 12.11 Netatmo 12.11.1 Netatmo Basic Information 12.11.2 Facial Recognition Product Introduction 12.11.3 Netatmo Production, Value, Price, Gross Margin 2015-2020 12.12 Safran 12.12.1 Safran Basic Information 12.12.2 Facial Recognition Product Introduction 12.12.3 Safran Production, Value, Price, Gross Margin 2015-2020 12.13 Techno Brain 12.13.1 Techno Brain Basic Information 12.13.2 Facial Recognition Product Introduction 12.13.3 Techno Brain Production, Value, Price, Gross Margin 2015-2020 12.14 Daon 12.14.1 Daon Basic Information 12.14.2 Facial Recognition Product Introduction 12.14.3 Daon Production, Value, Price, Gross Margin 2015-2020 12.15 Luxand 12.15.1 Luxand Basic Information 12.15.2 Facial Recognition Product Introduction 12.15.3 Luxand Production, Value, Price, Gross Margin 2015-2020 12.16 Animetrics 12.16.1 Animetrics Basic Information 12.16.2 Facial Recognition Product Introduction 12.16.3 Animetrics Production, Value, Price, Gross Margin 2015-2020 12.17 Aware 12.17.1 Aware Basic Information 12.17.2 Facial Recognition Product Introduction 12.17.3 Aware Production, Value, Price, Gross Margin 2015-2020 12.18 Aurora Computer Services 12.18.1 Aurora Computer Services Basic Information 12.18.2 Facial Recognition Product Introduction 12.18.3 Aurora Computer Services Production, Value, Price, Gross Margin 2015-2020 12.19 ArcSoft 12.19.1 ArcSoft Basic Information 12.19.2 Facial Recognition Product Introduction 12.19.3 ArcSoft Production, Value, Price, Gross Margin 2015-2020 12.20 Herta Security 12.20.1 Herta Security Basic Information 12.20.2 Facial Recognition Product Introduction 12.20.3 Herta Security Production, Value, Price, Gross Margin 2015-2020 12.21 Lathem Time 12.21.1 Lathem Time Basic Information 12.21.2 Facial Recognition Product Introduction 12.21.3 Lathem Time Production, Value, Price, Gross Margin 2015-2020 12.22 Idemia 12.22.1 Idemia Basic Information 12.22.2 Facial Recognition Product Introduction 12.22.3 Idemia Production, Value, Price, Gross Margin 2015-2020 12.23 FaceFirst 12.23.1 FaceFirst Basic Information 12.23.2 Facial Recognition Product Introduction 12.23.3 FaceFirst Production, Value, Price, Gross Margin 2015-2020 12.24 Cognitec Systems 12.24.1 Cognitec Systems Basic Information 12.24.2 Facial Recognition Product Introduction 12.24.3 Cognitec Systems Production, Value, Price, Gross Margin 2015-2020 12.25 XID Technologies 12.25.1 XID Technologies Basic Information 12.25.2 Facial Recognition Product Introduction 12.25.3 XID Technologies Production, Value, Price, Gross Margin 2015-2020

Chapter Thirteen: Industry Outlook continued

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List of tablesList of Tables and Figures Figure Product Picture of Facial Recognition Table Product Specification of Facial Recognition Table Facial Recognition Key Market Segments Table Key Players Facial Recognition Covered Figure Global Facial Recognition Market Size, 2015 2025 Table Different Types of Facial Recognition Figure Global Facial Recognition Value ($) Segment by Type from 2015-2020 Figure Global Facial Recognition Market Share by Types in 2019 Table Different Applications of Facial Recognition Figure Global Facial Recognition Value ($) Segment by Applications from 2015-2020 Figure Global Facial Recognition Market Share by Applications in 2019 Figure Global Facial Recognition Market Share by Regions in 2019 Figure North America Facial Recognition Production Value ($) and Growth Rate (2015-2020) Figure Europe Facial Recognition Production Value ($) and Growth Rate (2015-2020) Figure Asia Pacific Facial Recognition Production Value ($) and Growth Rate (2015-2020) Figure Middle East and Africa Facial Recognition Production Value ($) and Growth Rate (2015-2020) Figure South America Facial Recognition Production Value ($) and Growth Rate (2015-2020) Table Global COVID-19 Status and Economic Overview Figure Global COVID-19 Status Figure COVID-19 Comparison of Major Countries Figure Industry Chain Analysis of Facial Recognition Table Upstream Raw Material Suppliers of Facial Recognition with Contact Information Table Major Players Headquarters, and Service Area of Facial Recognition Figure Major Players Production Value Market Share of Facial Recognition in 2019 Table Major Players Facial Recognition Product Types in 2019 Figure Production Process of Facial Recognition Figure Manufacturing Cost Structure of Facial Recognition Figure Channel Status of Facial Recognition Table Major Distributors of Facial Recognition with Contact Information Table Major Downstream Buyers of Facial Recognition with Contact Information Table Global Facial Recognition Value ($) by Type (2015-2020) Table Global Facial Recognition Value Share by Type (2015-2020) Figure Global Facial Recognition Value Share by Type (2015-2020) Table Global Facial Recognition Production by Type (2015-2020) Table Global Facial Recognition Production Share by Type (2015-2020) Figure Global Facial Recognition Production Share by Type (2015-2020) Figure Global Facial Recognition Value ($) and Growth Rate of 2D Facial Recognition (2015-2020) Figure Global Facial Recognition Value ($) and Growth Rate of 3D Facial Recognition (2015-2020) Figure Global Facial Recognition Value ($) and Growth Rate of Thermal Face Recognition (2015-2020) Figure Global Facial Recognition Price by Type (2015-2020) Figure Downstream Market Overview Table Global Facial Recognition Consumption by Application (2015-2020) Table Global Facial Recognition Consumption Market Share by Application (2015-2020) Figure Global Facial Recognition Consumption Market Share by Application (2015-2020) Figure Global Facial Recognition Consumption and Growth Rate of Emotion Recognition (2015-2020) Figure Global Facial Recognition Consumption and Growth Rate of Attendance Tracking and Monitoring (2015-2020) Figure Global Facial Recognition Consumption and Growth Rate of Access Control (2015-2020) Figure Global Facial Recognition Consumption and Growth Rate of Law Enforcement (2015-2020) Figure Global Facial Recognition Consumption and Growth Rate of Others (2015-2020) Figure Global Facial Recognition Sales and Growth Rate (2015-2020) Figure Global Facial Recognition Revenue (M USD) and Growth (2015-2020) Table Global Facial Recognition Sales by Regions (2015-2020) Table Global Facial Recognition Sales Market Share by Regions (2015-2020) Table Global Facial Recognition Revenue (M USD) by Regions (2015-2020) Table Global Facial Recognition Revenue Market Share by Regions (2015-2020) Table Global Facial Recognition Revenue Market Share by Regions in 2015 Table Global Facial Recognition Revenue Market Share by Regions in 2019 Figure North America Facial Recognition Sales and Growth Rate (2015-2020) Figure Europe Facial Recognition Sales and Growth Rate (2015-2020) Figure Asia-Pacific Facial Recognition Sales and Growth Rate (2015-2020) Figure Middle East and Africa Facial Recognition Sales and Growth Rate (2015-2020) Figure South America Facial Recognition Sales and Growth Rate (2015-2020) Figure North America COVID-19 Status Figure North America COVID-19 Confirmed Cases Major Distribution Figure North America Facial Recognition Revenue (M USD) and Growth (2015-2020) Table North America Facial Recognition Sales by Countries (2015-2020) Table North America Facial Recognition Sales Market Share by Countries (2015-2020) Table North America Facial Recognition Revenue (M USD) by Countries (2015-2020) Table North America Facial Recognition Revenue Market Share by Countries (2015-2020) Figure United States Facial Recognition Sales and Growth Rate (2015-2020) Figure Canada Facial Recognition Sales and Growth Rate (2015-2020) Figure Mexico Facial Recognition Sales and Growth (2015-2020) Figure Europe COVID-19 Status Figure Europe COVID-19 Confirmed Cases Major Distribution Figure Europe Facial Recognition Revenue (M USD) and Growth (2015-2020) Table Europe Facial Recognition Sales by Countries (2015-2020) Table Europe Facial Recognition Sales Market Share by Countries (2015-2020) Table Europe Facial Recognition Revenue (M USD) by Countries (2015-2020) Table Europe Facial Recognition Revenue Market Share by Countries (2015-2020) Figure Germany Facial Recognition Sales and Growth Rate (2015-2020) Figure UK Facial Recognition Sales and Growth Rate (2015-2020) Figure France Facial Recognition Sales and Growth (2015-2020) Figure Italy Facial Recognition Sales and Growth (2015-2020) Figure Spain Facial Recognition Sales and Growth (2015-2020) Figure Russia Facial Recognition Sales and Growth (2015-2020) Figure Asia Pacific COVID-19 Status Figure Asia Pacific Facial Recognition Revenue (M USD) and Growth (2015-2020) Table Asia Pacific Facial Recognition Sales by Countries (2015-2020) Table Asia Pacific Facial Recognition Sales Market Share by Countries (2015-2020) Table Asia Pacific Facial Recognition Revenue (M USD) by Countries (2015-2020) Table Asia Pacific Facial Recognition Revenue Market Share by Countries (2015-2020) Figure China Facial Recognition Sales and Growth Rate (2015-2020) Figure Japan Facial Recognition Sales and Growth Rate (2015-2020) Figure South Korea Facial Recognition Sales and Growth (2015-2020) Figure India Facial Recognition Sales and Growth (2015-2020) Figure Southeast Asia Facial Recognition Sales and Growth (2015-2020) Figure Australia Facial Recognition Sales and Growth (2015-2020) Figure Middle East Facial Recognition Revenue (M USD) and Growth (2015-2020) continued

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NOTE: Our report does take into account the impact of coronavirus pandemic and dedicates qualitative as well as quantitative sections of information within the report that emphasizes the impact of COVID-19.

As this pandemic is ongoing and leading to dynamic shifts in stocks and businesses worldwide, we take into account the current condition and forecast the market data taking into consideration the micro and macroeconomic factors that will be affected by the pandemic.

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Impact Of Covid 19 On Facial Recognition Industry 2020 Market Challenges, Business Overview And Forecast Research Study 2026 Murphy's Hockey Law -...

Due to advanced neurotechnology, the development of human-machine interfaces and the betterment of the person's cognitive abilities is possible.

FREMONT, CA: Neurotechnology is fascinating as one of its goals is to directly wire up human brains to machines. Fundamental research is run to explore functions of the brain, decipher the neural code, and gets an improved understanding of diseases and disorders. Clinical applications of neurotechnologies provide alternatives to pharmaceutical methods and devices for diseases that have been fatal so far. The rapid development of this industry and the potential to increase human-human human-machine systems' communication abilities and the achievement of the information technology threshold of the scientific and technological progress makes it clear that the next technological revolution will be based on neurotechnology.

Previously, the medical field has focused on the fundamental potentials and perspectives of neurotechnology. However, it should be realized that very different processes have influenced this industry's development, which is still the powerful driver. It is about diagnosing and treating many neurodegenerative diseases, which are presently one of the main causes of deterioration in a person's quality of life. Currently, magnetic resonance imaging is used in many research and medical practices. The MR-image method enables to obtain 3D morphological and functional data at the millimeter and submillimeter levels.

However, the tradition of brain stimulation has more than 100 years of history, although quick development began after the development of imaging technologies. With the accumulation of new data, possibilities have emerged not only for analysis but also for accurate brain stimulation. The question of whether neurotechnologies should be leveraged or not is seamless to answer without putting it into the context of application instanced in the medical and non-medical field. No matter how the answer will be, this answer should not be given without knowledge about the possibilities, challenges, and threats of the technological solutions, without medical knowledge about potential risks, the patients' requirements, and potential alternative options. If everybody contributes their expertise and questions, the picture of neurotechnologies as allowing technology for new treatment options and better quality of life can become true, and patients cannot get fooled by wrong promises.

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Opportunities of Neurotechnology in Clinical Applications - Medical Tech Outlook

TAMPA, Fla.--(BUSINESS WIRE)--Neurolief Ltd., a neurotechnology innovator, today announces that it has entered into an exclusive agreement with Sawai Pharmaceutical Co., Ltd. for the development and marketing of Relivion, a non-invasive digital medical device for migraine and depression, in Japan.

Relivion is a non-invasive brain neuromodulation* device that is placed around the head and delivers unparalleled stimulation to the occipital and trigeminal nerves. This creates a cumulative effect by releasing neurotransmitters in the brainstem and modulating brain networks associated with control of pain and mood. The device is designed to allow patients to use Relivion at home, and share treatment data with their physician, in addition to uploading the data to the cloud database through a dedicated app. It is also designed to self-learn and analyze the treatments using AI technology in order to optimize the treatments for patients according to their symptoms.

*Neuromodulation: A therapeutic technology to modulate neurological activities through the administration of electric/magnetic stimuli or drugs.

With the view to launch Relivion in Japan, submissions to the Pharmaceuticals and Medical Devices Agency (PMDA) are expected for migraine by 2022 and depression by 2023. If Relivion is approved by the agency, it will be the only brain neuromodulation device available for treatment at home in Japan.

*In Europe, Neurolief obtained the CE Mark certification as a treatment device for migraine and is in preparation for the market launch. In the US, the application was filed to FDA in November 2020 as a 510(K) submission for migraine and is scheduled to be filed for depression by 2022.

By working with Sawai to introduce the Relivion neuromodulation device in Japan for use at home with doctor's supervision, we are widening treatment options for patients who are suffering from either migraine or depression.

About Neurolief

Dedicated to bringing relief to patients suffering from chronic neurological and neuropsychiatric disorders, Neurolief is creating a digital therapeutics platform of wearable clinically-proven neuromodulation solutions. This technology, which is made to be worn like a headset, is intended to offer highly effective, safe treatment options that work with current pharmaceutical therapies or may provide an alternative to these therapies. It is designed to concurrently neuromodulate major neural pathways in the head, and thereby affect brain regions that are involved in control and modulation of mood and pain. Neuroliefs technology is currently studied for patients with migraine and major depression, and future indications may include insomnia, ADHD and additional chronic pain and neuropsychiatric disorders. The company is based in Israel, with US operations in Tampa, FL and is made up of highly experienced professionals with a proven track record in neurosciences, neuromodulation technology and the neurotech devices industry. For more information, visit https://www.neurolief.com/

*The Trademark application for Relivion in Japan has been filed by Neurolief.

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Neurolief and Sawai Enter into Exclusive Development and Marketing Agreement for Relivion - Business Wire

Cereset Research shares brain maps of brain functional connectivity laterality in military-related traumatic stress

SCOTTSDALE, Ariz. (PRWEB) January 27, 2021

HIRREM (the legacy research technology of Cereset - a Brain State Company) was utilized by the Wake Forest School of Medicine to study symptoms of traumatic stress in military personnel before and after use of Cereset (legacy) intervention. (https://onlinelibrary.wiley.com/doi/10.1111/jon.12825)

Whole brain, resting state magnetic resonance imaging (MRI) was done pre- and post- Cereset intervention. Significant effects on brain network connectivity have been previously reported (https://onlinelibrary.wiley.com/doi/full/10.1111/jon.12571). For the current study, lateralization of brain connectivity was analyzed. Lateralization here refers to the distribution of brain connections within the right, and left side, or to the opposite side. This is important because common lobes in the right and left hemispheres of the brain execute different functions. Of note for these results, the parasympathetic division of the autonomic nervous system (which we think of as the brake to rest and digest) is managed primarily on the left, and the sympathetic division (which we think of as the gas to go) is driven primarily on the right. Thus, the dominant left is a freeze or numbing response indicator, and in contrast, a dominant right is the fight or flight response indicator.

Asymmetries were identified at baseline, along with changes in lateralization patterns after Cereset. Significant correlations were seen between whole-brain lateralization and symptoms of posttraumatic stress. These findings help to understand the effects of and how best to treat traumatic stress.

The brain is the organ of central command which activates and manages autonomic responses to trauma and stress. Results of this study support the model of bihemispheric autonomic management of traumatic stress (BHAM), proposed by Brain State and Wake Forest 6 years ago (https://www.frontiersin.org/articles/10.3389/fpsyg.2014.00843/full). Regulated connections of the brain appear to be the upstream driver of health and wellbeing. When connections between hemispheres are more balanced, individuals are healthier.

Of note is the basis for this brain movement towards a healthier pattern. Cereset merely reflects the brains own electrical patterns using engineered tones to represent dominant brain frequencies. The client receiving Cereset is comfortably seated in a reclining chair to listen to the brain generated tones or BrainEcho. This supports the brain to relax, to change, and to reset itself to improve balance and symmetry, which is associated with reduced symptoms of traumatic stress.

Many prior clinical studies have demonstrated benefits associated with the use of Cereset for symptoms of insomnia, depression, stress, anxiety, concussion, hot flashes, postural orthostatic tachycardia, and migraine. The current and previous clinical trials also included objective outcome measures such as heart rate variability to demonstrate significant improvement in autonomic function. Symptom benefits were durable for up to 6 months in the current study, and autonomic improvement was durable through the final follow-up visit at 4 months in a placebo-controlled trial for insomnia.

The addition of the MRI lateralization findings reported in this study and the correlation with symptoms not only support the BHAM model but also point to a mechanism of effect for the clinical benefits previously reported with Cereset. Symptoms associated with trauma, stress, and allostatic load now affect a majority of the population. Cereset noninvasively supports the brain to balance and regulate itself with resulting benefits for psychological symptoms of traumatic stress and improved autonomic function.

Funding for this study was provided by:The Susanne Marcus Collins Foundation Inc., Joint Capability Technology Demonstration Program within the Office of the Under Secretary of Defense, US Special Operations Command, and the Wake Forest Clinical and Translational Science Institute.

For more information about Cereset Research / HIRREM clinical research studies, and other innovations in closed-loop neurotechnology / balanced neuromodulation, visit: https://www.wakehealth.edu/hirrem https://cereset.com/research

ABOUT CERESETCereset is a wellness company that helps clients relax their brains to manage stress, restore hope and achieve restful sleep through its patented BrainEcho technology. Cereset empowers the brain to reset itself as it hears and sees its own reflection. The global technology leader in non-invasive brain self-restoration and optimization, Cereset enables the brain to fully relax and naturally rebalance itself from the inside out. There is no outside intervention, stimulus or medication of any kind the brain does its own work while the client naps or relaxes quietly in a comfortable chair. To schedule an appointment at a Cereset client center, or to learn more, visit https://cereset.com

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Brain signal processing may allow a more adaptive and immersive gaming experience

Gaming technology firm Valves Founder Gabe Newell urged developers to undertake brain-computer interface (BCI) studies, predicting that they will drastically change the gaming industry. According to Newell, gamers might soon be able to control their in-game movements via brain wave transmission thanks to emerging research and development in the field of BCIs, writes tvnz.com.

In a recent interview, Newell also announced an open-source project in partnership between Valve and the OpenBCI developer community. The project will allow creators to study and improve brain-signal processing in conjunction with VR headsets to enhance the gaming experience.

Aerendir has suggested biometric BCIs could upgrade mobile authentication security, and Neurotechnology launched a development kit for brainwave biometricslast year.

According to Valves Newell, the scanning process involves brainwaves being read through sensors placed in a headset. The gathered signals can then be interpreted to improve the gaming experience. Currently, data is taken from a players brain and body can be used to determine the individuals mental state. Excitement, boredom, surprise, and fear are only some of the emotions that can be captured using the proposed high-definition sensors.

Aside from allowing developers to personalize the gaming experience and make it more immersive, Newell also predicts that in the future these signals can be used to control in-game movements.

Were working on an open-source project so that everybody can have high-resolution [brain signal] read technologies built into headsets, in a bunch of different modalities, Newell added, If youre a software developer in 2022 who doesnt have one of these in your test lab, youre making a silly mistake.

Newell also predicts other applications resulting from BCI technology such as improved sleep and even emotional analysis and adjustments, at least some of which would presumably utilize brainwave data as biometrics. Asides from these benefits, he also added that BCIs are a vital element in improving artificial body parts.

The collaboration will allow Valve to incorporate OpenBCI products such as the planned Galea Headset to work in tandem with its signature Index VR headset.

biometric sensors | biometrics | brainwave | emotion recognition | gaming | open source | OpenBCI | wearables

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Valve sees brain-computer interfaces as the future of gaming - Biometric Update

Latest added Facial Recognition Market research study by MarketDigits offers detailed product outlook and elaborates market review till 2026. The market Study is segmented by key regions that is accelerating the marketization. At present, the market is sharping its presence and some of the key players in the study areGemalto NV, Ayonix Face Technologies, Cognitec Systems, NVISO SA., Daon, StereoVision Imaging, Techno Brain., Neurotechnology, Innovatrics.The study is a perfect mix of qualitative and quantitative Market data collected and validated majorly through primary data and secondary sources.

This report studies the Facial Recognition Market size, industry status and forecast, competition landscape and growth opportunity. This research report categorizes the Facial Recognition Market by companies, region, type and end-use industry.

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Scroll down 100s of data Tables, charts and graphs spread through Pages and in-depth Table of Content on Global Facial Recognition Market By Technology (2D and 3D Face Recognition, Facial Analyst), Component (Hardware, Software), Application (Homeland Security, Criminal Investigation, ID Management, Physical Security, Intelligent Signage, Web Application, Business Intelligence, Photo Indexing and Sorting), End Users (Government & Transportation, Military & Defense, BSFI, Retail, Hospitality), Geography (North America, South America, Europe, Asia-Pacific, Middle East and Africa) Industry Trends and Forecast to 2026. Early buyers will get 10% customization on study.

To Avail deep insights of Facial Recognition Market Size, competition landscape is provided i.e. Revenue Analysis (M $US) by Company (2018-2020), Segment Revenue Market Share (%) by Players (2018-2020) and further a qualitative analysis is made towards market concentration rate, product/service differences, new entrants and the technological trends in future.

Unlock new opportunities in Facial Recognition Market; the latest release fromMarketDigitshighlights the key market trends significant to the growth prospects, Let us know if any specific players or list of players needs to consider to gain better insights.

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Market Analysis:Global Facial Recognition Market

Global facial recognition market is set to witness a healthy CAGR of XX% in the forecast period of 2021 to 2027. The report contains data of the base year 2020 and historic year 2019. This rise in the market can be attributed due to rising demand for surveillance systems for enhancing safety and security

Few of the major competitors currently working in the globalfacial recognition marketareNEC Technologies India Private Limited, Aware, Inc., Gemalto NV, Ayonix Face Technologies, Cognitec Systems GmbH, NVISO SA., Daon, StereoVision Imaging, Inc., Techno Brain., Neurotechnology, Innovatrics, id3 Technologies, IDEMIA, Animetrics, Crunchbase Inc., Aurora Computer Services Limited, Nuance Communications, Inc., FaceFirst

Market Definition:Global Facial Recognition Market

Facial recognition is a technology which is used to recognize human face for different purposes. Facial recognition system uses biometrics software to match facial features or information from the recorded database. It is easy to integrate with existing security features. Facial recognition is generally used for security purposes. Facial recognition is also defined as an application based on biometric artificial intelligence that can define an individual uniquely by analyzing patterns based on the facial textures and shape of the individual.

Facial Recognition Market Restraints:

Research Methodology:Global Facial Recognition Market

Data collection and base year analysis is done using data collection modules with large sample sizes. The market data is analyzed and forecasted using market statistical and coherent models. Also market share analysis and key trend analysis are the major success factors in the market report. To know more please request an analyst call or can drop down your enquiry.

The key research methodology used byMarketDigits team is data triangulation which involves data mining, analysis of the impact of data variables on the market, and primary (industry expert) validation. Apart from this, other data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, Top to Bottom Analysis and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.

Facial Recognition Market Drivers:

Key Insights in the report:

An appropriate utilization of recognized statistical tools and coherent models for analysis and forecasting of market data makes this Facial Recognition Market report outshining. The report is generated by keeping in mind businesses of all sizes. Facial Recognition Market research report solves the problem of time consuming processes of acquiring market info very easily and quickly. You can take your business to the highest level of growth with this all-inclusive Facial Recognition Market research report. Clients can reveal best opportunities to be successful in the market with an excellent practice models and method of research used while generating this Facial Recognition Market report.

Table Of Content: Global Facial Recognition Market

Part 01: Executive Summary

Part 02: Scope Of The Report

Part 03: Global Facial Recognition Market Landscape

Part 04: Global Facial Recognition Market Sizing

Part 05: Global Facial Recognition Market Segmentation By Product

Part 06: Five Forces Analysis

Part 07: Customer Landscape

Part 08: Geographic Landscape

Part 09: Decision Framework

Part 10: Drivers And Challenges

Part 11: Market Trends

Part 12: Vendor Landscape

Part 13: Vendor Analysis

And More

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Facial Recognition Market Growth, Trends and Developments 20212027 | Gemalto NV, Ayonix Face Technologies, Cognitec Systems The Courier - The Courier

The head of video game giant Valve has revealed that the company is working on a way to connect human brains to computers in order to revolutionise gaming and fundamentally alter human experience.

Gabe Newell told New Zealands 1 News that Valve is working with neuroscience platform OpenBCI to develop an open source brain-computer interface (BCI) software.

One of the goals is to allow people to fully immerse themselves in video games through a VR-style headset, however Mr Newell claimed that the ultimate potential is nearly limitless.

Were working on an open source project so that everybody can have high-resolution [brain signal] read technologies built into headsets, in a bunch of different modalities, he said.

A lot of our product design discussions sound like science fiction Our ability to create experience in peoples brains that are not mediated through their meat peripherals will actually be better than is possible [with our senses].

A BCI headset design by OpenBCI that could integrate with a virtual reality device

(OpenBCI)

This would mean that by tapping directly into the part of the brain responsible for visual, audio or sensory feedback, a users experience would be vastly improved than what is delivered through their ears or eyes.

The real world will stop being the metric that we apply to the best possible visual fidelity, he said. The real world will seem flat, colourless, blurry compared to the experiences that youll be able to create in peoples brains.

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With BCIs, fairly quickly well be able to create experiences that are superior to [reality]. But thats not where it gets weird. Where it gets weird is that who you are becomes editable through a BCI.

The idea of editing emotions or thoughts through BCIs is not a new one and has previously been floated by Elon Musks neurotechnology startup Neuralink.

Neuralink demonstrated a working BCI device last year, which it had implanted in a pigs brain in order to monitor signals and activity.

During a presentation last August, Musk said the chip would be used to help solve brain and spine problems but could ultimately be used for a range of applications, such as summoning a self-driving Tesla telepathically.

You could solve blindness, you could solve paralysis, you could solve hearing, he said. In the future youll be able to save and replay memories Ultimately, you could download them into a new body or robot body."

A robot designed by Neuralink would insert the 'threads' into the brain using a needle

Neuralink

A fully implantable neural interface connects to the brain through tiny threads

Neuralink

Trials of Neuralink's fully implantable neural interface system will begin in 2021

Neuralink

Neuralink says learning to use the device is 'like learning to touch type or play the piano'

Neuralink

Valve is yet to announce any details about when a working device might be made commercially available, though Mr Newell hinted that it is unlikely to be before 2022.

Mr Newell also said that beyond gaming, advances with BCI technology would transform sleep into just an app that you run in order to maximise body recovery and performance.

The brains flexibility means you could even make people think they have tentacles instead of arms, he claimed, though he also warned that user acceptance of such technology depended entirely on trust.

Theres nothing magical about these systems that make them less vulnerable to viruses or things like that, he said.

People are going to have to have a lot of confidence that these are secure systems that dont have longterm health risks.

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Valve is building brain-computer interface for fully-immersive video games, president reveals - The Independent

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Key Plyares Analyis: Global Face and Voice Biometrics Market

3M Cogent (USA)NEC Corporation of America (USA)AcSys Biometrics Corp. (Canada)AGNITiO S.L. (Spain)Cognitec Systems GmbH (Germany)Nuance Communications, Inc. (USA)Eurotech S.P.A (Italy)Ivrnet Inc. (Canada)Kimaldi Electronics, S.L. (Spain)National Security Resources (USA)Neurotechnology (Lithuania)PSP Security Co. Ltd (Hong Kong)SAFRAN Group (France)Sensible Vision (USA)Sensory, Inc. (USA)Suprema, Inc. (Korea)VoiceTrUSt eServices, Inc. (Canada)VoiceVault, Inc. (USA)

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Face and Voice Biometrics Market Analysis by Types:

Face BiometricsVoice Biometrics

Face and Voice Biometrics Market Analysis by Applications:

Banking, Financial Services & Insurance (BFSI)Government & Law EnforcementMilitary & DefenseHealthcareCommercial

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Region Segmentation:

North America Country (United States, Canada)South AmericaAsia Country (China, Japan, India, Korea)Europe Country (Germany, UK, France, Italy)Other Country (Middle East, Africa, GCC)

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Major Points from Table of Content:

Section 1 Face and Voice Biometrics Product DefinitionSection 2 Global Face and Voice Biometrics Market Manufacturer Share and Market OverviewSection 3 Manufacturer Face and Voice Biometrics Business IntroductionSection 4 Global Face and Voice Biometrics Market Segmentation (Region Level)Section 5 Global Face and Voice Biometrics Market Segmentation (Product Type Level)Section 6 Global Face and Voice Biometrics Market Segmentation (Industry Level)Section 7 Global Face and Voice Biometrics Market Segmentation (Channel Level)Section 8 Face and Voice Biometrics Market Forecast 2020-2025Section 9 Face and Voice Biometrics Segmentation Product TypeSection 10 Face and Voice Biometrics Segmentation IndustrySection 11 Face and Voice Biometrics Cost of Production Analysis

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Face and Voice Biometrics Market Present Status, Revenue and Competitive Situation 3M Cogent (USA), NEC Corporation of America (USA), AcSys...

VILNIUS, Lithuania, Jan. 18, 2021 /PRNewswire/ --Neurotechnology, a provider of deep-learning-based solutions and high-precision biometric identification and object recognition technologies, today announced the release of theSentiVeillance 8.0software development kit (SDK). WithSentiVeillance SDK, developers can create identification solutions that use live video streams from digital surveillance cameras or video files. The latest version adds face detection and recognition of people who are wearing masks and includes new algorithms that improve license plate detection and recognition speed and accuracy. It also provides new features for vehicle and human (VH) mode, including car make and model estimation, vehicle angle estimation and cloth and gender estimations for pedestrians. It includes a new working mode combination enabling face and VH modes to be used together for fast and accurate identification.

SentiVeillance 8.0 provides identification and analytics from live digital surveillance streams or video files.

"I am very grateful for all the hard work our team put into this latest release that enhances speed and accuracy and provides compelling new ways to use our software,"said Vytautas Pranckenas, SentiVeillance product lead for Neurotechnology."There has never been a more important time for reliable recognition solutions that can adapt to new conditions, such as people wearing masks."

The new SentiVeillance mode combination (face and VH) allows tracking of the subject even when the face is no longer visible functionality that is particularly useful in scenarios where tracking a person's position is important.

BIOMETRIC FACIAL RECOGNITIONThe high reliability of SentiVeillance's biometric facial identification algorithm allows it to be used with large watch-list databases, both for identifying a person who is on a list and adding new faces from video streams to watch-lists. It tracks identified faces as they move around the camera's field of view and continues tracking even if a person moves behind an object and re-appears. It is effective both close-in and at a distance when using high-resolution cameras. SentiVeillance can perform gender classification, evaluate a person's age, identify facial expressions (e.g. smile, open mouth, closed eyes) and detect particular attributes, such as if the person is wearing a mask, glasses or sunglasses and whether they have a beard or mustache.

VEHICLE and HUMAN DETECTION AND MOVEMENT TRACKING (VH)SentiVeillance detects both moving and static vehicles or people in a scene and performs object classification and tracking until the subjects disappear. In addition to pedestrian detection and vehicle classification by type, it provides identification of the specific vehicle make and model as well as its orientation. For pedestrians, SentiVeillance identifies different types of clothing and provides gender prediction. The algorithm also returns an estimation of paint color for vehicles and predominant clothing color for pedestrians, and it determines the vector in which they are moving (e.g. north, south, southwest).

AUTOMATIC LICENSE PLATE RECOGNITION (ALPR)The new ALPR capability in SentiVeillance automatically detects and reads vehicle license plates, recording the information from both stationary and moving vehicles within the scene. The latest release is up to 2 times faster for CPU uses and up to 5 times faster when a GPU is used. Accuracy testsreach 99.1% for >200 pixel width license plates and 88.7% for license plates captured from far away (<100 pixel width).

The latter two modes (VH and ALPR) can be used together to create larger, more varied solutions. For example, when conventional ALPR is used for road tolls, automatic car washes or paid parking systems, users might try to avoid paying by altering or exchanging license plates. Stolen vehicles might also have their license plates changed. When using multiple analytics in concert, the resulting solution could match and verify plate numbers with other characteristics of the vehicle, such as type and color, through queries of previously stored values or vehicle registration databases.

The new SentiVeillance is designed to run on multi-core processors for fast performance and can process video data from multiple cameras simultaneously using a common PC (current generation i7 CPU with 8 or more cores) and can utilize multiple graphics processing units (GPUs) to achieve even better performance. It can be used with large surveillance systems, incorporating many cameras and data-processing nodes. Developers have many and varied options in the creation of scalable, cost-effective solutions for their customers.

THERMAL FACES SAMPLEThe new SentiVeillance SDK package contains a precompiled sample with source codes and device integration for the Mobotix m16 camera with thermal sensor. It shows functionality for face tracking, mask estimation and temperature readings, and it allows the setting of temperature thresholds or estimating deviations from averages. The sample is created to help with automatic entrance control.

ABOUT NEUROTECHNOLOGYNeurotechnology is a developer of high-precision algorithms and software based on deep neural networks and other AI-related technologies. The company was launched in 1990 in Vilnius, Lithuania, with the key idea of using neural networks for various applications, such as biometric person identification, computer vision, robotics and artificial intelligence. Since the first release of its fingerprint identification system in 1991, the company has delivered more than 200 products and version upgrades. More than 3,000 system integrators, security companies and hardware providers in more than 140 countries integrate Neurotechnology's algorithms into their products. The company's algorithms have achieved top results in independent technology evaluations, including NIST MINEX, PFT, FRVT, IREX and FVC-onGoing.

Media Contact

Jennifer Allen Newton Bluehouse Consulting Group, Inc. +1-503-805-7540 jennifer (at) bluehousecg (dot) com

SOURCE Neurotechnology

https://www.neurotechnology.com

Here is the original post:

Neurotechnology Releases New SentiVeillance 8.0 SDK for Identification and Analytics Using Live and Video Streams - PRNewswire

Neurotechnology has released the latest version of its SentiVeillance software development kit. SentiVeillance 8.0 will enhance the utility of the computer vision platform for people who are wearing masks, and will also improve its performance with license plates and vehicles.

The SDK provides customers with a full suite of computer vision applications, including facial recognition and license plate detection. The upgrades will allow the platform to identify covered faces during the COVID-19 pandemic. It can also determine whether or not someone is wearing mask to make sure people are complying with public safety guidelines. The solution can be used for surveillance and access control, and can read attributes like gender and age while simultaneously tracking someones movements through a large space.

The updated vehicle features will provide similar tracking capabilities for cars. SentiVeillance 8.0 is able to identify the make and model of a car, and can estimate other details like paint color and the direction a vehicle (or a pedestrian) was headed when it left the cameras field of view. As a result, the system can follow a vehicle even if the driver tries to change their license plate to evade detection, especially when used in conjunction with facial recognition.

Having said that, SentiVeillance 8.0 will improve Neurotechnologys ability to recognize license plates. The new SDK is two times faster with a CPU and five times faster with a GPU, and is 99.1 percent accurate when close up (>200 pixel width) and 88.7 percent accurate at distance (<100 pixel width).

SentiVeillance can be used to search for people on watch lists, or add people to a watch list based on their activities. It is also comes with integration code for the Mobotix m16 camera, which is built with a thermal sensor and offers temperature detection capabilities.

This latest release enhances speed and accuracy and provides compelling new ways to use our software,said SentiVeillance Product Lead Vytautas Pranckenas.There has never been a more important time for reliable recognition solutions that can adapt to new conditions, such as people wearing masks.

Neurotechnology released the twelfth edition of its MegaMatcher biometric platform in September. The company is now one of the many companies that has added mask and temperature detection capabilities during the pandemic, joining a list that already includes vendors like CyberLink and VSBLTY.

January 18, 2021 by Eric Weiss

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Neurotechnology Improves Mask and Vehicle Tracking Capabilities with SentiVeillance 8.0 - findBIOMETRICS