The global emotion detection and recognition market are estimated to grow at a CAGR of nearly 19.2% during the forecast period. The major factors contributing to the market growth include rising smartphone penetration, increasing demand for wearable devices, and emerging application in the retail sector. There is a rising demand for AI-enabled wearable devices primarily in adults owing to the increasing focus on fitness and health monitoring. AI-enabled wearables support in increasing functionalities and experience of end-users by delivering real-time insights, statistics along with the support to make informed decisions. AI technology utilizes the power of machine learning and natural language processing and is used in various sectors including consumer electronics, healthcare, gaming, and education.  

AI technology has been proved to be an essential tool in the healthcare industry as it utilizes software and algorithms to analyze complex medical data. The demand for technologically advanced miniaturized electronics and various other tools has been increasing over the last decade. As a result, the manufacturers of AI-based tools are focusing on the development of AI-based software and wearable devices coupled with the tools that can support to track and monitor daily activities more effectively. Wearable devices have garnered attention for emotion recognition applications. Emotion detection and monitoring which is based on normally utilized wearable devices can have an essential role in human-computer interaction and psychological health monitoring.

Most existing wearable devices for emotion recognition have relied on bioelectrical signals. The bioelectrical signals are electronic signals that indicate physiological responses, such as a pulse or a sweating response. These signals originate from changes in the autonomous nervous system (ANS), which is a control system that regulates human bodily functions.  The device provides emergency alerts and communicates the readings to the physicians. Further, camera modules have been used in commercial wearable devices. In particular, they have been primarily used in head-mounted wearable devices to capture the user’s perspective, and there have also been emotion recognition studies by using the captured pictures. Therefore, the rising demand for wearable devices is supporting to drive market growth. 

Market Segmentation

The global emotion detection and recognition market is segmented into software and end-user. Based on software, the market is classified into facial recognition, speech and voice recognition, biosensing, and others. Based on end-user, the market is classified into commercial, defense, industrial, and others. 

Facial Recognition is Anticipated to Witness Significant Growth During the Forecast Period 

Facial recognition is anticipated to hold significant share in the market during the forecast period owing to the increasing application of facial recognition technology in smartphones and iPhones. In April 2018, in India, Oppo launched F7 powered by AI technology for selfie photography in addition to several AI-powered operational features. This supports to make selfies more real, natural, and personalized. Besides, AI technology offers more accurate facial recognition capability, self-learning capabilities based on user preferences along with added fun features. 

The growing R&D for smartphones and iPhones is boosting the adoption of AI technology. Additionally, the government and security forces make use of facial recognition feature to identify citizens and tracking down criminals, as well as prevent terrorist activities. Facial recognition may go beyond physical structure to emotional analysis as it may enable to detect whether a person is angry or stressed. Therefore, facial recognition is expected to be a crucial application in mobile devices and government applications.

Global Emotion Detection and Recognition Market Share by Software, 2019 (%)

Regional Outlook

Geographically, the market is classified into four major regions, including North America, Europe, Asia-Pacific, and Rest of the World (RoW). In 2019, North America is anticipated to hold a significant share in the market owing to the presence of major retailers such as Walmart and Kroger Co., and significant focus on surveillance activities in the region. Walmart and other retailers in the US are using facial recognition technology to detect expressions of shoppers. The technology employs video cameras at stores that monitor customers' movements and facial expressions to detect the level of satisfaction. Further, Asia-Pacific is estimated to witness significant growth in the market owing to the presence of major smartphone manufacturers and the rising number of smart city projects in the region.

Global Emotion Detection and Recognition Market Growth, by Region 2020-2026

Market Players Outlook 

The major players operating in the market include Microsoft Corp., Google LLC, IBM Corp., Tobii AB, and Affectiva Inc. The market players are constantly focusing on gaining significant market share by adopting mergers & acquisitions, geographical expansion, product launch, and partnerships and collaborations. For instance, in April 2019, Affectiva Inc. declared that it has closed funding of $26 million, led by Aptiv PLC, as well as Motley Fool Ventures, Trend Forward Capital, and CAC, which resulted in total investment amounted to $53 million. This financing will enable Affectiva to evolve, speed up and scale its human perception AI technology in the automotive industry, as well as other fields such as social robotics, conversational interfaces, and market research.

The Report Covers

• Market value data analysis of 2019 and forecast to 2026.
• Annualized market revenues ($ million) for each market segment.
• Country-wise analysis of major geographical regions.
• Key companies operating in the global emotion detection and recognition market. Based on the availability of data, information related to pipeline products, and relevant news is also available in the report.
• Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
• Analysis of market-entry and market expansion strategies.
• Competitive strategies by identifying ‘who-stands-where’ in the market.