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AI in Computer Vision Market is projected to grow up to 27% CAGR during the forecasting period 2021-2027.
The ongoing investment in AI techniques by key OEMs such as Apple, Samsung, Huawei, and Google is driving the debut of computer vision technology in smartphones. The latest generation of smartphones includes advanced cameras with better resolutions, which gather more data and increase the quality efficiency of image perception and also the accuracy of machine vision. Google has worked on the world's first tango-enabled smartphone, the Lenovo Phab 2, as well as the ASUS ZenFone AR, while Apple has integrated 3D sensing with the front-facing camera in the iPhone X. Apple's approach has sparked a surge in 3D sensing use. All of these new technological developments are made feasible by computer vision. Computer vision is a thriving industry, as this technology is used in a variety of common items. Visual search elements are being added to the websites of e-commerce businesses such as Asos and Alibaba in order to improve and personalise the purchasing experience. With the release of the latest iPhone, Apple debuted its facial recognition capability. It is a technology made feasible by their acquisitions of companies such as PrimeSense, RealFace, and Faceshift. The increased need for integrated reality is a key element driving the AI in computer vision industry. The computer vision software propels VR and AR to the next level of development, which some refer to as Merged Reality (MR). The VR and AR systems can: perceive the environment and direct the user away from obstacles such as walls, products, or other users; detect the movement of the user's eye and body and adapt the VR environment accordingly; and provide guidance and directions with the help of the external environment by mapping cameras and sensors, as well as eye tracking solutions and gyroscopes to position the user.

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Key Driving Factors:Increased Demand for Emotion AI Emotion

AI employs computer vision technology to scan face appearances and eye trends in photographs and videos to read an individual's emotional responses. Emotion AI, a London-based startup, uses a PC or cell phone camera to track the facial expressions of a sample crowd watching a specific promotion. Rising demand for artificial intelligence for emotion analysis is fueling the integration of artificial intelligence with computer vision, which is contributing to market growth.

Increasing demand for computer vision systems in non-traditional and emergent applications

Inspection, identification, measurement, and product location are some of the key applications of computer vision systems in many industries. Aside from Market research , all AI-enabled vision systems have some way of developing new ones, such as 3D model construction, retail, medical imaging, optical character recognition, automotive safety, surveillance and traffic monitoring, morphing, and augmented reality.

This report offers the major market player’s profiles, such as NVIDIA (US), Intel Corp. (US), Microsoft Corp. (US), IBM Corp. (US), Qualcomm (US), AWS (US), Xilinx (US), Google (US), Facebook (US), Basler (Germany), Hailo (US), and GROQ (US). CEVA, Inc. (US), AMD (US), Graphcore (England), Groopic (US), Leap Motion (US), Algolux (US), Athena Security (US), LionBridge AI (US), Vizseek (US), Oculus (US), Curemetrix (US), Trivision (Denmark), Robotic Vision Technologies (US), AMP Robotics (US), Zivid (Norway), Inspekto (UK), and Creative Virtual (UK).

Based on End user: The artificial intelligence in computer vision research report is classified into several segments based on the end user, including automotive, sports and entertainment, robotics and machine vision, security and surveillance, government and defence, and others. As a result of the increasing investment in the above-mentioned industries in order to automate processes and manufacture error-free goods, the usage of artificial intelligence (AI) based computer vision hardware and software has increased over time.
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