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Super-resolution is very important in recognizing suspects face in video surveillance system. In this paper, we present an improvement of image super-resolution based on sparse signal representation. The issue of how to deal efficiently with sparse feature has great significance on the quality improvement of generated high resolution image. We propose to use Elastic net to solve sparse representation...
Conventional surveillance systems usually use multiple screens to display acquired video streams and may cause trouble to keep track of targets due to the lack of spatial relationship among the screens. This paper presents an effective and efficient surveillance system that can integrate multiple video contents into one single comprehensive view. To visualize the monitored area, the proposed system...
Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for observing humans' appearance, movements and activities, thus providing analytical information for advanced human behaviour analysis and realistic human modelling. In order for the system to function, it requires robust method for detecting human...
In this paper a novel method for view independent human movement representation and recognition, exploiting the rich information contained in multi-view videos, is proposed. The binary masks of a multi-view posture image are first vectorized, concatenated and the view correspondence problem between train and test samples is solved using the circular shift invariance property of the discrete Fourier...
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