Subtractive clustering of vertices for CPCA based animation geometry compression

Authors:
Sanjib Das;Prabin Kumar Bora;Anup Kumar Gogoi
Affiliations:
IIT Guwahati, Guwahati, India;IIT Guwahati, Guwahati, India;IIT Guwahati, Guwahati, India
Venue:
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Year:
2010

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Abstract

In the Clustered PCA(CPCA) algorithm for compressing the animation geometry sequences, the vertex trajectories are clustered using the K-means algorithm followed by the Principal Component Analysis(PCA) of the clusters. However, the compression performance of the method is constrained by the initial random selection of the cluster centres. This paper presents a stable method for initializing the cluster centres by the subtractive clustering technique prior to the application of the K-means algorithm. Simulation results on some test animation sequences show better performance of the CPCA with the proposed initialization compared to the CPCA with random initialization.