According to the recent research report "AI in Computer Vision Market by Component (Hardware, Software), Vertical (Automotive, Sports & Entertainment, Consumer, Robotics & Machine Vision, Healthcare, Security & Surveillance, Agriculture), and Region - Global Forecast to 2023", the AI in computer vision market is expected to be valued at USD 3.62 Billion in 2018 and is expected to reach USD 25.32 Billion by 2023, at a CAGR of 47.54% between 2018 and 2023.
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Opportunity: Development of machine learning regarding vision technology
Applications that require speed, high resolution, and good sensitivity to light are expected to push the vision system technology forward. The future development of technologies, individual components, or complete systems is expected to concentrate mainly on enhanced resolution and speed, greater sensitivity, easier integration capabilities, and faster interfaces. These innovations also ensure constant advancements in new industries and for non-industrial applications. Advancement in camera dynamic range and resolution, computational cameras, real-time detection of moving objects, use of color information, analysis of point clouds, and cloud computing of machine vision are some of the technological developments that the computer vision industry is going to experience in the future.
For instance, Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models. It classifies images into thousands of categories, detects individual objects and faces within images, and finds and reads printed words contained within images. It builds metadata on the user’s image catalog, or enable new marketing scenarios through image sentiment analysis. Furthermore, it analyzes images uploaded through a request or integrates with your image stored in Google Cloud.
In August 2016, Ford (US) acquired SAIPS (Israel) to integrate human-like intelligence into machine learning components of driverless car systems. SAIPS technology focuses on image- and video-processing algorithms and deep learning that enables processing and classifying input signals. The SAIPS technology enables on-board interpretation of data captured by sensors in Ford’s self-driving cars, and turns that data into usable information for the car’s virtual driver system.
This has enabled the development of machine learning into autonomous vehicles using vision technology.
Challenge: Premium pricing of AI hardware
AI is rapidly being incorporated into diverse applications in the cloud and at the network’s edge. AI hardware needs to be miniaturized into low-cost, reliable, high-performance chips to increase the adoption of AI. Companies such as Google (US), Apple (US), and Huawei (China) are including AI hardware components and software solutions in their flagship smartphones. These smartphones use AI in all applications ranging from imaging and photography to power efficiency and security. According to the recent trend, it can be predicted that the AI chipset market will grow rapidly by 2022; the price will drop approximately below USD 25 per chip, and the open-source ecosystem for real-time Linux on DL SOC will emerge. This as a result will trigger mass adoption of AI edge-client chipsets for mobiles and PCs/laptops, e.g., Snapdragon, an application processor that gives mobile phones the computing power to run sophisticated applications and software. Snapdragon is also used by other companies such as Toshiba (Japan), Acer (Taiwan), and Google (US). The short-term impact of premium cost of edge-based processors is expected to be a major challenge. However, in the long term, the overall economy of scale of the manufacturers of AI processors is expected to minimize the overall impact during the forecast period.
Consumer vertical expected to hold the largest share during the forecast period
Key factors contributing to the growth of the AI in computer vision market in the consumer vertical is the addition of AI capabilities to smartphones, which will help change mainly 2 aspects: user–machine interaction and context-personalized openness. User machine interaction will improve the efficiencies between the user and their phone across text, voice, image, video, and sensors, whereas the latter will actively provide services and aggregated information across apps, content, third-party features, and native features.
AI in computer vision market in North America expected to hold the largest share in 2017
North America is expected to hold the largest market share in 2017. Startups in the US are receiving funds from various organizations to imply the AI technology in autonomous drones and other flying vehicles. The major focus is to overcome challenges faced by industrial drones in terms of reliability, safety, and autonomy. Thus, companies have come up with solutions that combine computer vision and deep learning algorithms and identify potential hazards, and speed and distance. The market for AI in computer vision in APAC is expected to grow at the highest CAGR during the forecast period and surpass North America by 2023.
Major players operating in the AI in computer vision market include NVIDIA (US), Intel (US), Qualcomm (US), Apple (US), Alphabet (US), Microsoft (US), Facebook (US), Wikitude (Austria), Xilinx (California), Basler (Germany), Teledyne Technologies (US), Cognex (US), General Electric (US), and Avigilon (Canada).
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