Vision Processing Unit Market: Projection of Each Major Segment over the Forecast Period
Albany, NY -- (SBWire) -- 04/25/2018 --Vision Processing Unit (VPU) refers to a dedicated processor which produces high quality of images with ambient light and also reduces the power consumption by freeing up the CPU and GPU space thereby improving the overall performance of the system in which it is implemented. The Vision Processing Unit (VPU) market is primarily driven by the increasing adoption of machine vision systems across wide range of industry verticals including consumer electronics, automotive, healthcare, and manufacturing among others.
Additionally, the advent of Artificial Intelligence (AI) and machine learning technologies required to program the systems is expected to assist the growth of the market.
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Various robots having vision capabilities are increasingly being implemented across the manufacturing and automobile industries for various purposes which include inspection of the products, quality check, assisting in the various stages of production, and security and surveillance among others. Furthermore, the growing developments in the automobiles particularly, the autonomous vehicles is anticipated to impact the market positively.
Machine Vision systems are used in the automobiles as a part of advanced driver assistance system (ADAS) which leads to improved safety while travelling. ADAS systems keep the driver aware while driving by giving inputs such as nearby vehicles, automatic braking systems, providing alerts pertaining to any objects, pedestrians, or vehicles nearby and so on.
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Depending on application, the global VPU market has been segmented into smartphones, digital cameras, automobiles, wearable devices, drones, robots, and medical devices. In 2016, the smartphone segment was the highest revenue generating segment. Vision processing units are increasingly being used in smartphones to improve their photography capabilities and increase the functionality of the cameras which is fuelling the growth of the market. The smartphone segment is estimated to grow at CAGR of 16.95 % over the forecast period from 2017 to 2025.
Based on the end use verticals, the market has been divided into consumer electronics, automotive, industrial, and healthcare and others. In 2016, the consumer electronics segment was the topmost revenue generating segment owing to the increased implementation of VPUs in electronic devices such as smartphones, wearable devices, digital cameras, drones where low power consumption is a primary concern.
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In terms of global geography, the market has been divided into North America, Europe, Asia Pacific, Middle East & Africa and South America. In 2016, North America was the topmost revenue generating region followed by Europe. Asia Pacific region is expected to grow at highest CAGR from 2017 to 2025 owing to the bolstering growth in the automotive and electronics industry. Asia Pacific region is expected to grow at a CAGR of 19.08% over the forecast period.
The key trends prevalent in the Vision Processing Unit market are the strategic alliances of established as well as small players with their peers in the semiconductor segment in order to establish footprint in the vision processing and machine vision space and gain greater share globally.
The global vision processing unit market is expected to witness innovative products and M&A by major market players in order to establish footprint in the machine vision space and gain an increased market share. For instance, In August 2017, Movidius launched its new vision processing unit (VPU), Myriad X, which is the world's first system-on-chip (SOC) with a reliable Neural Compute Engine to enhance the deep learning inferences at the edge.
The key players profiled in the global Vision Processing Unit market include Movidius, Inc., Synopsys, Inc., MediaTek, Inc., Imagination technologies Limited, Ceva Inc., VeriSilicon Ltd among others. In a bid to stay ahead of the competition, it can be seen that the key players are entering into mergers and acquisition deals with the peers as well as smaller players.
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