Clustering dynamic textures with the hierarchical EM algorithm

Antoni B. Chan, Emanuele Coviello, Gert. R. G. Lanckriet
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
The dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model has been applied to a wide variety of computer vision problems, such as motion segmentation, motion classification, and video registration. In this paper, we derive a new algorithm for clustering DT models that is based on the hierarchical EM algorithm. The proposed clustering algorithm is capable of both clustering DTs
more » ... and learning novel DT cluster centers that are representative of the cluster members, in a manner that is consistent with the underlying generative probabilistic model of the DT. We then demonstrate the efficacy of the clustering algorithm on several applications in motion analysis, including hierarchical motion clustering, semantic motion annotation, and bag-ofsystems codebook generation.
doi:10.1109/cvpr.2010.5539878 dblp:conf/cvpr/ChanCL10 fatcat:duiaptenfjayrcycgkcqtuncui