Computer Vision Market Report Overview:
Computer vision is a scientific stream that deals with the technology and theory for the creation of artificial systems that collects information from multidimensional data and images.
The technology has gained immense traction as the need for equipping computers with a vision similar to humans has intensified over the years. Market Research Future (MRFR)’s latest report on the global computer vision market has projected striking growth within the market at a CAGR of 31.65% over the forecast period of 2017-2023. MRFR further projects the market to reach a valuation of USD 48.32 Bn by the end of 2023.
Computer vision provides the advantages of high accuracy in terms of identifying real-world objects, and potential applications in face and gesture recognition have helped the market earn many accolades. Computer Vision Market is an emerging technology which is highly connected with augmented reality and virtual reality. Significant progress in AR and VR, along with their subsequent adoption is likely to boost the growth of the market. However, computer vision technology is still in its nascent stage and would need to overcome various technical challenges and slow adoption rate to enter the mainstream. Meanwhile, the prevalent trend of investing in tech start-ups among technology leaders is likely to provide a thrust to the growth of the market.
Basler AG (Germany), National Instruments (U.S.), Autoliv Inc. (U.S.), Keyence Corporation (Japan), Cognex Corporation (U.S.), Intel Corporation (U.S.), Nvidia Corporation (U.S.), IBM Corporation (U.S.),Microsoft Corporation (U.S.), and Sony Corporation (Japan) are the key players in the computer vision market.
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The global computer vision market has been segmented based on component, application, and verticals.
- By component, the computer vision market has been segmented into software and hardware. The hardware segment is currently leading the market owing to the increased affordability of semiconductor devices. the hardware segment is anticipated to reach USD 26.43 Bn by the end of 2023.
- By application, the computer vision market has been segmented into face recognition, gesture recognition, character recognition, and others. The gesture recognition segment is anticipated to be the largest as well as the fastest growing segment over the forecast period. The growth of the segment can be attributed to the less number of devices required for successful recognition, identification, and commencement of interaction. Moreover, rapid progress in performance and accuracy is likely to boost the growth of the segment.
- By vertical, the computer vision market has been segmented into agriculture, automotive, healthcare, entertainment, transportation, and others. The automotive segment is likely to expand a CAGR of 33.86% over the forecast period and capture the largest share of the global market. The entertainment sector is also estimated to showcase rapid growth over the forecast period due to the growing popularity of augmented reality applications.
Region-wise, the computer vision market has been segmented into North America, Rest-of-the-World (RoW), Europe, and Asia Pacific (APAC).
The deployment of computer vision across diverse industries in North America has positioned it as the leading computer vision market. Growing implementation of surveillance analytics for tracking of user behavior is also a key factor driving the growth of the market.
The APAC computer vision market is anticipated to exhibit considerable growth over the forecast period. The rising number of start-ups focused on augmented and virtual reality technologies can be credited for the growth of the market.
June 2019 – researchers have developed two different computational methods that provide cameras the ability to see around corners. The new computer vision innovations have been presented at the Computer Vision and Pattern Recognition (CVPR) conference in Long Beach, California.
A team from the University of Montreal, Princeton University and Algolux have reconstructed high-quality images of traffic signs and other 3D objects that were captured on-vehicle cameras and smartphones. Similarly, researchers from Carnegie Mellon University, the University of Toronto and University College London have developed a non-line-of-sight (NLOS) imaging technique which is capable of computing millimeter- and micrometer-scale shapes of curved objects.
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- Semiconductor product designers and fabricators
- Developers of machine vision-related applications
- Providers of machine vision-related components and solutions
- Technology standard organizations, forums, alliances, and associations
- Technology investors
- Universities and research organizations
- Government bodies
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