Learning Video Manifolds for Content Analysis of Crowded Scenes
Myo Thida, How‐Lung Eng, Dorothy Monekosso, Paolo Remagnino · IPSJ Transactions on Computer Vision and Applications · 2012
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.