As the huge demand for the public security and protection, more and more surveillance cameras are installed in the places of public activities, such as school, hospital, business street, residential block and park, etc. This produces massive surveillance videos and presents formidable challenges to video browsing, storage and retrieval. This thesis focuses on video condensation and pedestrian attribute classification. The main works and contributions of this thesis are summarized as follows. 1. A fast video condensation solution based on the online video condensation framework is proposed. The solution mainly includes the multi-thread design and the accelerating strategy. The video condensation task is broken down into three parallel steps: 1) the tube (object sequence) generation step, including the online background generation, moving object segmentation and sticky tracking; 2) the tube rearrangement step, using the online content-aware tube filling algorithm to rearrange tubes' appearing time labels; 3) the object stitching step, stitching rearranged tubes into background images to produce condensation video frames. The three steps are parallelly implemented by using the multi-thread technique. Moreover, a number of techniques are introduced to enhance the system on speed and memory consumption, including: 1) a GPU(Graphic Processing Unit) accelerated scale invariant local ternary pattern (SILTP) feature based background subtraction algorithm is used for moving object segmentation; 2) an online background generation method is applied to generate a constantly updated background image, consuming low memory cost; 3) an effective memory buffer design based on the producer-consumer model is used to control the memory balance between different multi-thread modules. 2. A novel multi-channel joint video synopsis (JVS) method is proposed. The traditional video synopsis (TVS) is aimed for videos captured by a single camera, thus can not present the overall activities of moving objects in a camera network. To solve this issue, in the JVS, a global energy function used for tube rearrangement is designed. The global energy function includes occlusion cost and chronological disorder cost terms. The occlusion cost term based on the relative occlusion degree is designed for tubes extract from the same camera view, which makes the cost range is considerable with the chronological disorder cost range, thus it is independent with the resolution of the input video. ...
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