Thida, Myo, How-Lung, Eng, Monekosso, Dorothy and Remagnino, Paolo (2012) Learning Video Manifolds for Content Analysis of Crowded Scenes. IPSJ Transactions on Computer Vision and Applications, 4 . pp. 71-77. [Journal article]
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In this paper, we propose a new approach for recognizing group events and abnormality detection in a crowded scene. A manifold learning algorithm with temporal-constraints is proposed to embed a video of a crowded scene in a low-dimensional space. Our low dimensional representation of a video preserves the spatial temporal property of a video as well as the characteristic of the video. Recognizing video events and abnormality detection in a crowded scene is achieved by studying the video trajectory in the manifold space. We evaluate our proposed method on the state-of-the-art public data-sets containing different crowd events. Qualitative and quantitative results show the promising performance of the proposed method.
|Item Type:||Journal article|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Mathematics
|Research Institutes and Groups:||Computer Science Research Institute > Smart Environments|
Computer Science Research Institute
|Deposited By:||Dr Dorothy Monekosso|
|Deposited On:||10 Jul 2012 12:09|
|Last Modified:||10 Jul 2012 12:09|
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