Aligned Cluster Analysis for temporal segmentation of human motion

Feng Zhou, Fernando De la Torre, Jessica K. Hodgins
2008 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition  
Temporal segmentation of human motion into actions is a crucial step for understanding and building computational models of human motion. Several issues contribute to the challenge of this task. These include the large variability in the temporal scale and periodicity of human actions, as well as the exponential nature of all possible movement combinations. We formulate the temporal segmentation problem as an extension of standard clustering algorithms. In particular, this paper proposes
more » ... Cluster Analysis (ACA), a robust method to temporally segment streams of motion capture data into actions. ACA extends standard kernel kmeans clustering in two ways: (1) the cluster means contain a variable number of features, and (2) a dynamic time warping (DTW) kernel is used to achieve temporal invariance. Experimental results, reported on synthetic data and the Carnegie Mellon Motion Capture database, demonstrate its effectiveness.
doi:10.1109/afgr.2008.4813468 dblp:conf/fgr/ZhouTH08 fatcat:fhodsqak7bewnkwatvpsw3xlpi