The universal Emotion Detection and Recognition report has key information about the industry, market segmentation, important facts and figures, expert opinions, and the latest developments across the globe. This marketing report is a definitive source of information about the industry, important facts and figures, expert opinions, and the latest developments across the globe. This global market report examines the market with respect to general market conditions, market status, market improvement, key developments, cost and profit of the specified market regions, position and comparative pricing between major players. Emotion Detection and Recognition market analysis report suggests that the global market is anticipated to witness a relatively higher growth rate during the forecast period.
Increase in the demand for wearable devices, growing adoption of internet of things technology by small and medium scale organisations and surge in the need for technological advancement to standardize emotion detection are the major factors attributable to the growth of the emotion detection and recognition market. Data Bridge Market Research analyses that the emotion detection and recognition market will exhibit a CAGR of 15.35% for the forecast period of 2021-2028. This means that the emotion detection and recognition market would stand tall at a market value of USD 49.36 billion by 2028.
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Market Overview:
The emotion detection and recognition technology is based on image processing technologies that are used to detect the emotions of a human face. The emotion detection and recognition technology is used to identify the behavioural patterns along with analysing the gestures and postures of the body.
Global Emotion Detection and Recognition Market Scope and Market Size
The emotion detection and recognition market is segmented on the basis of software tool, technology, service, application area and end user. The growth amongst the different segments helps you in attaining the knowledge related to the different growth factors expected to be prevalent throughout the market and formulate different strategies to help identify core application areas and the difference in your target market.
· By the software tool, the emotion detection and recognition market is segmented into facial expression and emotion recognition, gesture and posture recognition, bio-sensing software tools and apps, speech and voice recognition.
· Based on technology, the emotion detection and recognition market is segmented into feature extraction and 3D modelling, bio sensors technology, pattern recognition, natural language processing, machine learning and others.
· On the basis of service, the emotion detection and recognition market is segmented into storage and maintenance and consulting and integration.
· Based on the application area, the emotion detection and recognition market is segmented into medical emergency and healthcare, marketing and advertising, law enforcement, surveillance and monitoring, entertainment and consumer electronics, robotics and e-learning and others.
· On the basis of end user, the emotion detection and recognition market has been segmented into enterprises, defense and security agencies, commercial, industrial, personal users, government, retail, entertainment, transportation and others.
The major players covered in the emotion detection and recognition market report are Affectiva., Noldus Information Technology bv., Kairos AR, Inc., Takema Intelligent Technology (Shanghai) Co., Ltd., NVISO SA., Vocalis Health., Crowd Emotion Limited, Emotient, Inc., Eyeris Technologies, Inc., Realeyes, Sentiance NV., Sightcorp., SkyBiometry UAB, Tobii AB, Mad Street Den Inc., AdMobilize, Emotion Research Lab, Quantic Dream., Emotibot Technologies Limited and iMotions among other domestic and global players. Market share data is available for global, North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America separately. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.
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