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2016

A Diffusion and Clustering-Based Approach for Finding Coherent Motions and Understanding Crowd Scenes

7 years 11 months ago
A Diffusion and Clustering-Based Approach for Finding Coherent Motions and Understanding Crowd Scenes
Abstract—This paper addresses the problem of detecting coherent motions in crowd scenes and presents its two applications in crowd scene understanding: semantic region detection and recurrent activity mining. It processes input motion fields (e.g., optical flow fields) and produces a coherent motion filed, named as thermal energy field. The thermal energy field is able to capture both motion correlation among particles and the motion trends of individual particles which are helpful to discover coherency among them. We further introduce a two-step clustering process to construct stable semantic regions from the extracted time-varying coherent motions. These semantic regions can be used to recognize pre-defined activities in crowd scenes. Finally, we introduce a cluster-and-merge process which automatically discovers recurrent activities in crowd scenes by clustering and merging the extracted coherent motions. Experiments on various videos demonstrate the effectiveness of our ap...
Weiyao Lin, Yang Mi, Weiyue Wang, Jianxin Wu, Jing
Added 11 Apr 2016
Updated 11 Apr 2016
Type Journal
Year 2016
Where TIP
Authors Weiyao Lin, Yang Mi, Weiyue Wang, Jianxin Wu, Jingdong Wang, Tao Mei
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