Seattle, WA -- (SBWIRE) -- 10/28/2019 -- Emotion recognition is a technique that provides advanced image processing and allows a program to "read" the emotions, such as anger, sadness, fear, joy, disgust, surprise, trust, and so on, of a human face. Various players are experimenting by combining image processing techniques with sophisticated algorithms that have emerged over the past 10 years. This has been implemented to understand more about a persons feeling with the help of a facial image or video.

The global emotion detection and recognition market is driven by substantial growth of Internet of Things (IoT), increase in popularity of wearable technology, and rise in usage of smartphone globally. However, high cost of application, functional requirements, and misinterpretation in analysis of emotions hamper the emotion detection and recognition market growth.

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Factors that are expected to impact the global emotion detection and recognition market during the forecast period are growth of IoT technology, high popularity of wearable technology, and increase in adoption of smartphones. However, the impact of factors, such as high cost of application and functional requirement, is expected to diminish during the forecast period.

IoT involves monitoring and responding of all devices in accordance with the emotion, mood, and actions of a person. There are devices that pass information to one another without human intervention, such as input from a sensor that regulates the output of an industrial process at a remote installation. Emotion-sensing technology has witnessed a rapid shift from an experimental phase to reality. For instance, the way in which questions are asked and emotions are displayed on the mood-tracking app (Moodnotes) is designed to understand the mental health of the user.

Wearable technology includes sensors for tracking information that detects physical traces such as heart rate, blood pressure, and skin temperature, providing clues about mood. Human emotions, such as facial expressions, tone of voice, body postures, and gestures, are accompanied by physiological changes, which can be measured by wearable gadgets to derive a conclusion.

Emotion detection and recognition systems perform several functions to detect emotion. Inclusion of such functions into EDR systems incurs high cost to the system. The requirement of emotion detection applications is of two types: functional and non-functional. Functional requirements include acquiring face images, image pre-processing, face detection, managing users face images; while non-functional requirements include usability, scalability, convenience to capture image, guidelines for acquiring face images, and others.

Key Benefits:

- This study comprises analytical depiction of the global emotion detection and recognition market with current trends and future estimations to depict the imminent investment pockets.
- The overall market potential is determined to understand the profitable trends to gain a stronger foothold.
- The report presents information related to key drivers, restraints, and opportunities with a detailed impact analysis.
- The current market is quantitatively analyzed from 2016 to 2023 to highlight the financial competency of the emotion detection and recognition market.
- Porters Five Forces analysis illustrates the potency of the buyers and suppliers in the industry.

Significant players operating in the emotion detection and recognition industry are Affectiva, Beyond Verbal, Noldus Information Technology, Sentiance, Sightcorp, Realeyes, CrowdEmotion, Kairos AR, Inc., nViso SA., and SkyBiometry.

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