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This paper proposes a motion-focusing method to extract key frames and generate summarization synchronously for surveillance videos. Within each pre-segmented video shot, the proposed method focuses on one constant-speed motion and aligns the video frames by fixing this focused motion into a static situation. According to the relative motion theory, the other objects in the video are moving relatively...
Many works of conventional surveillance have focused on people tracking, behavior or event detection, gait or face based recognition, etc. However, role identification is also very important in video surveillance but usually paid less attention. In this paper, we propose a collaborative multi-camera system to identify people with specific roles using a causal network to form a best identification...
The moving objects are what attract most attention in the video surveillance system, and also the key part for study. Currently, the video surveillance system relies much on the subjective initiative of the observers while having the real-time surveillance. In this study, applying the mixture Gaussian model algorithm, the profile image of the moving objects in the picture got from the video surveillance...
We present a scaled down version of a human detection and tracking system designed to run on relatively low-end machines of developing countries. The system uses sequence of monocular images of a single, fixed surveillance camera to extract data of moving objects. A linear motion model coupled with pre-computed average color intensities is used to track the detected subjects across a series of frames...
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