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As with the development of computer technology and informatization, network technique, sensor technique and communication technology become three necessary components of information industry. As the core technique of sensor application, signal processing mainly determines the sensor performances. For this reason, study on signal processing mode is very important to sensors and the application of sensor network. In this paper, we introduce a new sensor coarse signal processing mode based on adaptive genetic algorithm. This algorithm selects crossover, mutation probability adaptively and compensates multiple operators commutatively to optimize the search process, so that we can obtain the global optimum solution. Based on the proposed algorithm, using auto-correlative characteristic parameter extraction method, it achieves smaller test error in sensor coarse signal processing mode of processing interference signal. We evaluate the proposed approach on a set of data. The experimental results show that, the proposed approach is able to improve the performance in different experimental setting. [ABSTRACT FROM AUTHOR]

In this article, we proposed a surveillance video retrieval method based on detection of moving objects and researched on key problems in surveillance video, such as moving objects detection, video segmentation, selection and description of key frames, and measurement of feature similarities. We detected moving objects via movement detection algorithm based on codebook, and realized automatic segmentation of surveillance video via calculating present Frame Movement Amount based on the foreground and background information in movement detection. After the above process, we proposed a video retrieval method based on the combination of SIFT and color feature. [ABSTRACT FROM AUTHOR]