Various applications under the hood will drive the growth of embedded video. Processors for applications such as self-parking will grow strongly this year and in the future.
According to IMS Research, a subsidiary of IHS, various applications under the hood of automobiles will be an important driver of growth in the embedded vision field this year. Embedded vision dominates various devices that can "see" and interpret data from computer vision software.
In 2013, the operating income of dedicated processors used for offline warning and self-parking and other applications under automotive hoods is expected to reach US $ 151 million, compared with US $ 137 million and US $ 126 million last year and 2011 respectively. The field will continue to expand in the next few years, and the growth rate will remain at 6-9%, indicating that the prospect of embedded vision is very bright. Embedded vision is one of the fastest growing trends in technology. By 2016, the operating income of dedicated processors for applications under the hood is expected to reach US $ 187 million. As shown in Figure 4, the six-year compound annual growth rate is equivalent to 8.2%.
Figure: Global revenue of dedicated processors for applications under the hood (in millions of dollars)
Embedded vision enables the machine to understand its environment through visual means, combining high-performance image enhancement application processors, digital signal processors and field programmable gate arrays with computer vision software. Although image sensors have been around for quite a long time, such sensors cannot "see" without an advanced processor to help interpret the image. Only by combining sensing and interpretation of images can vision be formed, and the emergence of powerful low-cost processors has created the possibility for a wide range of embedded systems to gain visual capabilities.
Automotive and factory automation systems are key markets
Automobile vision system is one of the formed embedded vision markets. In the field of automotive vision systems, the current trend is to embed solutions in multiple small markets. The situation is changing. An increasingly comprehensive intelligent market is being formed, and new applications with higher levels of intelligence are being developed. Older application models may use many processors and cameras to manage various individual performance requirements and solutions, while integrated vision systems use multi-core high-performance processors. The number of cameras used is greatly reduced, making them more complex and compact. solution.
Embedded vision has been used in automotive vision applications, such as offline warning, collision avoidance, self-parking and blind spot warning. The overall effective market in this regard is very large, with 94.7 million light vehicles likely to be installed with such systems in 2016, compared with 71.1 million in 2011.
Embedded vision is also used in a variety of industrial security applications, which is another powerful force driving growth in this area.
For example, in factory automation, applications include smart vision sensors, machine vision cameras, and compact vision systems. By 2016, machine vision hardware shipments may reach 6.1 million, compared with 3.3 million in 2011.
The other two emerging markets for embedded vision are video content analysis systems. In this regard, network monitoring hardware shipments may reach 38.7 million in 2016, up from 11.2 million in 2011; military aviation, military-grade applications are expected to use processors It reached 92 million in 2016, up from 83.5 million in 2011.
In some emerging areas, embedded vision is also growing
In addition to the established market, embedded vision is also growing in areas such as gesture recognition, augmented reality and digital signage. These markets are not yet mature, but they are likely to become established markets within three to six years. For example, in gesture recognition and augmented reality applications, embedded vision can be used in gaming systems, smartphones, cameras, and video cameras. In digital signage applications, embedded vision can be used for commercial signs that can be targeted for marketing based on video content analysis.
The third market area for embedded vision is in emerging markets. In the longer term, such as seven to ten years, these markets are expected to reveal opportunities. These emerging markets include facial recognition, such as automated teller machines for identity verification; transportation, such as self-guided cars and smart infrastructure; and medical, patient monitoring and interaction based on vision.
IHS believes that with the continuous development of embedded vision technology, the market for various new applications will continue to expand. The coordination between computer vision and embedded applications will continue to develop, embedded vision will find new applications, and new vision applications will also emerge.
Disruptive technologies such as embedded vision usually originate from the fusion of applications and hardware. However, how and when these technologies can enter new application areas requires a comprehensive and comprehensive observation. Otherwise, how can people predict that computer video applications will be combined with mobile phone processors to allow cars to "see"?
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