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Emotion Detection and Recognition Technology Market Size Projected To Rise Lucratively During 2016–2

Author: Harshal Naik
by Harshal Naik
Posted: May 13, 2019

Emotion recognition is mainly defined as a technique used in software programs that can help a program to understand what exactly human emotions are, by detecting them in a detailed manner. This is possible by using advanced image processing methods. There are several companies who are currently conducting numerous experiments for emotional recognition, especially by creating complex algorithms. In this way, the scientists mainly aim to understand more about a person’s facial expressions, moods, and micro-facial movements, and how to integrate these aspects with technology.

Although still in its infant years, emotional detection and recognition technology has been used for a while in several devices. This is mainly with respect to facial detection unlock features present in smartphones, computer monitors, tablet computers, and several other gadgets. With a rapid pace of innovation in this technology, scientists may soon find a way to unlock more uses of recognizing human emotions and incorporating them in better ways.

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Software programs used for emotion detection and recognition technology have become highly capable of detecting even the slightest facial changes. These changes may be a part of the commonly known expressions linked with emotions like anger, happiness, sadness, and excitement, or may exist independently. These are called micro-expressions, and they are small cues to how a person might fake a facial expression without affecting the underlying body language and gestures. As the latter are inherently natural, the emotion detection and recognition technology can also be used for security purposes.

Emotional detection and recognition technology can also be used in a more controlled manner, wherein the users are aware of what type of emotion they are projecting. The best example of this technique is the latest Facebook update that makes users put on a reaction to posts, other than the traditional ‘thumbs up’ sign. The more frequently a person expresses any posts with particular emotions, there are higher chances of Facebook’s algorithm analyze the emotions, and show more related posts for the user.

Global Emotion Detection and Recognition Technology Market: Overview

Emotion recognition is a technology being used in software that offers a program with the access to read and understand emotions on a human face. This is done using advanced image processing technologies. Facial sensing and bio-sensing software are gaining immense popularity and are used in a large number of industry verticals. As a result, this market is expected to witness substantial growth in the coming years.

The research study offers a detailed analysis of the global emotion detection and recognition technology market. Additionally, a comprehensive vendor analysis of the market has been provided to offer a clear picture of the market for readers and market players.

Global Emotion Detection and Recognition Technology Market: Drivers and Restraints

Advancement in technology is considered as a key factor encouraging the growth of the global emotion detection and recognition technology market. In addition, the increasing popularity of wearable technology is expected to offer promising opportunities for the prominent players operating in the global market. A substantial growth of the Internet of Things technology and a tremendous rise in the use of smartphone across the globe are anticipated to fuel the growth of the global market in the next few years.

On the flip side, the global emotion detection and recognition technology market is estimated to face several challenges in the coming years. The high cost of application and several function requirements are predicted to restrict the growth of the market throughout the forecast period. Nonetheless, the robust pace of development and the introduction of new and effective products are estimated to supplement the growth of the global market in the next few years.

Global Emotion Detection and Recognition Technology Market: Region-wise Outlook

On the basis of geography, the research study has classified into Europe, Asia Pacific, North America, and the Rest of the World. Among these, Europe and North America are anticipated to witness a strong growth in the next few years. The robust growth of these two regions can be attributed to the technological advancements and the rising demand for wearable devices. The presence of prominent players in these two regions is another factor augmenting the growth of the emotion detection and recognition technology market in Europe and North America.

Furthermore, Asia Pacific is likely to contribute towards the development of the global market in the next few years. This region is estimated to register a healthy growth in the coming years, thanks to the growing demand from India, Japan, and China. A significant rise in the technology and research and development sector is anticipated to fuel the growth of the emotion detection and recognition technology market in Asia Pacific in the coming years.

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The competition in the emotion detection and recognition technology market across the globe is expected to grow at a fast pace in the next few years. The increasing implementation of this technology in diverse applications is anticipated to encourage the growth of the overall market in the near future. The rising focus by the leading players on research and development activities and innovations is predicted to accelerate the growth of the overall market.

Some of the leading players operating in the global market for emotion detection and recognition technology are Tobii, Affectiva, Emotient, Noldus, Sight Corp, and Eyeris. The research study presents a thorough overview of the competitive landscape, focusing on the company profiles and the business strategies adopted by them in order to sustain in the competitive scenario. In addition, the product portfolio, financial overview, and the SWOT analysis of these players have been provided in the research study.

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Author: Harshal Naik

Harshal Naik

Member since: Apr 26, 2019
Published articles: 94

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