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论文类型：期刊论文

发表时间：2016-10-01

发表刊物：MULTIMEDIA TOOLS AND APPLICATIONS

收录刊物：SCIE、EI、Scopus

卷号：75

期号：19

页面范围：11661-11682

ISSN号：1380-7501

关键字：Action matching; Projective invariance; Cross-view; Characteristic number

摘要：Existing action matching methods from the geometric respect typically assume the collinearity or coplanarity for view invariance. These assumptions curb the application to uncontrolled action patterns. In this paper, a new projective invariant named characteristic number (CN) is used, which can be used to describe 3D non-coplanar points. For motion trajectories of actions, we propose the temporal CN (TCN) for individual joint point of a human body in temporal series. This view-invariant feature can characterize an action well with limited number of joints(a single one in our experiments). In addition to TCN, we are also able to define the spatial characteristic number (SCN) on several (five in our paper) joint points in the spatial domain for one frame. SCN works complementary to temporal features, when limited snapshots of an action are available. We validate both SCN and TCN on the widely used CMU Motion Capture Database (Mocap) database, KTH Multiview Football Dataset II and IXMAS dataset. The promising recognition results indicate the invariance to varying viewpoints compared with the state-of-the-art. The results on CMU and KTH database corrupted by noise show the robustness to noise.