Object Detection — Model of Foreground and Background —

Object detection is a basic problem of image understanding in a real environment. It can be defined as means to segment an image into foreground regions and background regions. There can be two approaches in object detection. One is to use characteristics of appearance of target objects. The other is to user characteristics of background. Those characteristics are referred as to foreground model and background model respectively. Those models are obtained not only by prior knowledge but also by examples gathered on line under operation. In this survey, we focus on background model and foreground model proposed in recent object detection researches. We also discuss model acquisition, learning, and classifier employed in them.

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