Emotion Detection And Recognition Market Size, Key Developments,...

Emotion Detection And Recognition Market Size, Key Developments, Company Overview, Competitive Landscape, Demand and Trends by Forecast to 2030

Posted 2022-12-02 02:52:22

Overview:

The global market report with details on the emotion detection and recognition market is slated to cross a valuation of USD 65 billion by 2023, during which it will attain 39% CAGR to cover the global forecast period of 2018 to 2023. Market Research Future (MRFR) announced that this growth would be backed by factors like the growing inclusion of top-end technologies, assistance from artificial intelligence, changing scenarios after the COVID-19 crisis, demands from the security agencies, a constant influx of funding, and others.

Competitive Landscape:

The global market review on the emotion detection and recognition market includes latest changes made by companies like Eyeris (U.S.), Kairos Ar. Inc. (U.S.), Affectiva (U.S.), Emotient, An Apple Company (U.S.), nViso. (Switzerland), Realeyes (U.K.), Skybiometry (Lithuania), Noldus (Netherlands), Sentiance (Belgium), Sightcorp (Netherlands), and others for a better understanding of the market flow.

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Segmentation:

The global market report on the emotion detection and recognition market has been segmented by analysts on the basis of technology, software tool, application, service, and end user. These segments can contribute in significant ways in the forming of strategies that could ensure a better market stand in the coming days.

By technology, the global market report on the emotion detection and recognition market includes segments like biosensor technology, pattern recognition, feature extraction and 3D modeling, machine learning, natural language processing (NLP), and others.
By software tool, the report includes an analysis of the emotion detection and recognition market speech and voice recognition, biosensing software tools and apps, and facial expression recognition.
By service, the review of the market includes storage and maintenance, and consulting and integration.
By application, the emotion detection and recognition market review studies law enforcement, surveillance & monitoring, marketing & advertising, media & entertainment, and others. The law enforcement, surveillance & monitoring segment is expected to provide a substantial tailwind to the market.
By end user, the emotion detection and recognition market report included industrial, defense & security agency, commercial, enterprises, and others. The defense & security agency segment is expected to make sure the market gets proper space for growth.

Regional Analysis:

North America and Europe would use their structural advantage, capacity to fund such projects, inclination towards the inclusion of such advanced technologies, and others to ensure steady growth for the respective regional markets. South Korea, China, India, Japan, and others would dominate the Asia Pacific market.

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Industry News:

In September 2020, NtechLab announced that it has raised $15 million from two sovereign wealth funds who have shown interest in backing the company’s testing on its aggression detection technology and opening of offices that could sell its biometric facial recognition and machine learning technologies across the globe.

This funding came from the Russian Direct Investment Fund and a Middle-Eastern investor.

In September 2020, an ethical AI startup, Percepta Labs, is expected to receive around $1 million in investment from ADT Commercial, a company known as a commercial security provider. The company is planning to work with Percepta in a bid to develop and test the company’s technology that can be used for anonymizing gender, race, and age from various facial recognition data. The process could make a path for the socially responsible AI technology to commercialization. Percepta’s proprietary technology has this ability to detect shoplifting incidents in real-time and it uses advanced action recognition techniques to do that. This is an endeavor to scrub demographic data from the received feed.