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Video content analysis (also Video content analytics, VCA) is the capability of automatically analyzing video to detect and determine temporal and spatial events. This technical capability is used in a wide range of domains including entertainment,〔(KINECT ), add-on peripheral for the Xbox 360 console〕 health-care, retail, automotive, transport, home automation, safety and security.〔(VCA usage increase in British Security ), BSIA report〕 The algorithms can be implemented as software on general purpose machines, or as hardware in specialized video processing units. Many different functionalities can be implemented in VCA. Video Motion Detection is one of the simpler forms where motion is detected with regard to a fixed background scene. More advanced functionalities include video tracking and egomotion estimation. Based on the internal representation that VCA generates in the machine, it is possible to build other functionalities, such as identification, behavior analysis or other forms of situation awareness. VCA relies on good input video, so it is often combined with video enhancement technologies such as video denoising, image stabilization, unsharp masking and super-resolution. ==Functionalities== Several articles provide an overview of the modules involved in the development of video analytic applications.〔(Nik Gagvani ), Introduction to Video Analytics〕〔(Cheng Peng ), Video Analytics〕 This is a list of known functionalities and a short description. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Video content analysis」の詳細全文を読む スポンサード リンク
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