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Market Overview
Emotion recognition is a technique used that offers advanced image processing. It allows a program to read different emotions of a human face, such as anger, sadness, joy, disgust, surprise, fear, trust, and so on.
Various players are experimenting by combining image processing techniques with sophisticated algorithms that have emerged over the past decades. The technique has been implemented to examine more about a person's feelings with the help of a facial image or video. Based on software tools, facial expression tools hold the market's largest share. Facial expressions are motions that assist the response to a given speech. Facial recognition software is an important component of the emotion detection and recognition system because it makes it easier to recognize emotions and responses from facial expressions and provides real-time findings.
North America has shown significant market share due to developed countries, such as U.S. and Canada, which are home to the largest retail markets, with demand for IoT and smart wearables and high ad spending.
Global Emotion Detection And Recognition Market Dynamics
The growing adoption of wearable devices drives the market share for emotion detection and recognition.
The growing adoption of wearable devices drives the market share for emotion detection and recognition
Sensors in wearable electronics detect physical traces like blood pressure, heart rate and skin temperature, offering hints about mood. Human emotions, including facial expressions, voice tones, bodily postures and gestures, are accompanied by physiological changes that can be detected by wearable devices and used to conclude.
As per the GSMA, the IoT connections market is expected to reach 25 billion by 2025 and the IoT market revenue is expected to reach US$ 1.1 trillion within the same period. The applications of devices are projected to trickle down to practically every end-user industry globally as IoT demand grows.
The number of connected wearable devices is also increasing. Sensors on these devices capture, monitor and analyze vital biological signs like heart rate, pulse and body temperature. According to Cisco Systems, the number of connected wearable devices globally will reach 1,105 million by 2022. Furthermore, many smart wearable device providers have included bio trackers in their health tracking features. Huami's latest smartwatch, the Amazfit GTS, is equipped with a Huami Bio Tracker Optical sensor that allows for 24-hour precise heart rate tracking.
ECG monitors have gained popularity and are being included in wearables, which can measure electrocardiograms, send the results to doctors for diagnosis and provide emergency alarms. Such market developments provide a technology infrastructure for emotion recognition that is well-established.
High application costs and functional requirements create a huge challenging atmosphere for the growth of emotion detection and recognition
The emotion detection and recognition systems technology is intricate and requires complex programming algorithms. The design and manufacture of these systems is a capital-intensive process. The component prototyping and system integration costs can cost hundreds of thousands of U.S. dollars.
The systems must undergo long-ranging real-world field tests before wider deployment. It must recognize and detect emotions under various lighting conditions and usage periods. The tests can last anywhere from days to months and even years, requiring a lot of capital expenditure.
The components used in the system are highly specialized and developed by niche firms with long-term partnerships with global tech giants. It relegates the research and development of emotion detection and recognition systems to big tech conglomerates and crowds out smaller players. Innovation in this sector is also stifled as big firms generally prefer gradual evolutionary changes which guarantee steady revenue streams instead of risking disruptive, revolutionary changes.
The high costs in the field act as an entry barrier to new companies and start-ups, stifle innovation and prevent other industries' wider adoption of the systems. It remains a key challenge for the long-term growth of the market.
COVID-19 Impact Analysis
The global emotion detection and recognition market experienced a decline in 2020 owing to COVID-19's impact. Governments globally imposed strict lockdowns of varying durations starting from March 2020 to curb the spread of the emerging COVID-19 pandemic.
The lockdowns caused disruptions in the operations of emotion detection systems-making companies. Many companies had to scale down or suspend operations owing to government regulations. The development of an emotion detection and recognition system is a capital-intensive process. With the reduction in revenues, many industries had to scale back, suspend or postpone capital investments due to the effects of the pandemic.
U.S., one of the largest emotion detection and recognition markets, had a massive surge in cases from April 2020. The second wave of pandemics hit North America and Europe in late 2020. China, another major market, emerged from COVID-19 restrictions relatively early by June 2020 and demanded to recover somewhat. However, overall global demand remained subdued from 2020 through early 2021.
The collapse in demand from the end-use industries caused a severe disruption in the global emotion detection and recognition market. The research and development of new technologies and the introduction and field testing of new systems were delayed. Many small & medium-scale enterprises in emotion detection and recognition system supply chain were facing bankruptcy due to the reduced demand.
Global Emotion Detection And Recognition Market Segment Analysis
The global emotion detection and recognition market are segmented on a software tool, technology, application and region.
Smart cars, smart speakers and other applications increasingly use voice-controlled technology, which is boosting the segmental growth of the product
The global emotion detection and recognition market are segmented based on software tools: facial emotion recognition, vocal recognition and others (image, biometrics). Vocal recognition dominates the market of the mentioned software tool. Speech and voice recognition assist in recognizing phrases or words and converting such phrases or words into a machine-readable format. Users can control devices using speech and voice because the audio and text received by such devices are immediately transformed into a machine-friendly format, allowing humans to manage devices without wasting time and effort using other devices such as mouse and keyboards. The mentioned factor is a primary driver of the global speech and voice recognition market's growth, which is expected to continue during the projected period.
Smart cars, smart speakers and other applications increasingly use voice-controlled technology. Several businesses, including the smartphone industry, assistance applications, embedded devices, dictation appliances and others, use voice-controlled and speech-recognition technologies. According to an Adobe Analytics survey, voice recognition is most commonly used on smart speakers and smartphones today for browsing music and asking fun questions, followed by internet searches, maps and directions, weather forecasts, news and other things. The mentioned points significantly increased the speech and voice recognition industry throughout the predicted period.
Telepaper, a Malaysia-based thermal products manufacturer, offers a wide variety of sizes for Emotion Detection And Recognition rolls and there are available in different product types such as 1-ply, 2-ply and 3-ply. The NCR paper is also offered in multiple color selections, including White, Gold, Yellow, Pink, Blue, Green and Canary.
Global Emotion Detection And Recognition Market Geographical Analysis
Due to rising criminal activity in Asia Pacific, there are many investments in security and monitoring, which raises public awareness leading to creating growth prospects for the emotion detection and recognition market
Due to rising criminal activity, many investments in security and monitoring raise public awareness. As a result of these factors, the market in the region is experiencing growth potential. Facial recognition technology is utilized in various industries, including banking, healthcare, government, defense & public spaces, such as airports and country and state borders.
Due to rising criminal activity, many investments in security and monitoring raise public awareness. As a result of these factors, the market in the region is experiencing growth potential. Passengers at Narita Global Airport in Japan can board flights using facial biometrics rather than a passport or boarding card check. The face recognition system improved convenience for travelers, particularly those who attended the 2020 Tokyo Summer Olympics and Paralympics. According to the Biometric update, a similar fast-matching facial recognition solution from NEC will be employed for athlete screening. The face recognition market in Asia-Pacific is being driven by the numerous applications of facial recognition technology in various nations.
Countries like South Korea and Singapore have developed pandemic-resistant technologies. For example, in South Korea, an app called Corona 100m has been developed to inform users if they get within 100 meters of a corona-affected person.
Global Emotion Detection And Recognition Market Competitive Landscape
The global emotion detection and recognition market are highly competitive with local and global key players. The key players contributing to the market's growth are Uniphore, International Business Machines Corporation, Microsoft, Noldus Information Technology bv., NEC Global, Cipia Vision Ltd., Google, Intel Corporation, Apple Inc, Affectiva and others.
The major companies are adopting several growth strategies, such as product launches, acquisitions and collaborations, contributing to the global growth of the emotion detection and recognition market.
• For instance, in April 2020, Intel Corporation introduced the OpenVINO toolkit with the Intel RealSense Viewer. The result is a convolutional neural network (CNN) implementation optimized for Intel processors (CPU, GPU or other accelerators). It could use specific optimizations that boost scalability while improving throughput and speed. Once a face has been detected, the toolkit can quickly execute various tasks, including feature extraction (jawline, eyes, nose), emotion and orientation.
Uniphore
Overview: Uniphore is engaged in providing conversational service automation, which combines the power of artificial intelligence, machine learning and automation technology. The company partners across various industries to transform customer experiences.
Uniphore enables businesses to deliver transformational customer service through an automation platform where digital agents take over transactional conversations from humans during calls and accurately predict emotion, language and intent. The company offers emotion detection and recognition solutions for education, HR, sales & marketing and healthcare industries. Uniphore has U.S., Singapore, Israel, Japan, Spain and India offices.
Product Portfolio: Emotion AI: Emotion AI technology restores the ability to read nonverbal cues like tone of voice, facial expressions and attentiveness. It also improves the EQ abilities by integrating the real-time analysis of facial expressions, voice tonality and sentiment to enhance every conversation.
Key Development
• On January 21, 2021, Uniphore announced the acquisition of Emotion Research Lab, a software developer that uses AI and ML to identify emotion and engagement levels in real-time over video-base.
Why Purchase the Report?
• Visualize the global emotion detection and recognition market segmentation by software tool, technology, application and region, highlighting key commercial assets and players.
• Identify commercial opportunities in the emotion detection and recognition market by analyzing trends and co-development deals.
• Excel data sheet with thousands of global emotion detection and recognition market-level 4/5 segmentation points.
• PDF report with the most relevant analysis cogently put together after exhaustive qualitative interviews and in-depth market study.
• Product mapping in excel for the key product of all major market players
The global emotion detection and recognition market report would provide approximately 61 market data tables, 53 figures and 219 pages.
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