Automatic moving object extraction using x-means clustering

Abstract

The present paper proposes an automatic extraction technique of moving objects using x-means clustering. The proposed technique is an extended k-means clustering and can determine the optimal number of clusters based on the Bayesian Information Criterion(BIC). In the proposed method, the feature points are extracted from a current frame, and x-means clustering classifies the feature points based on their estimated affine motion parameters. A label is assigned to the segmented region, which is obtained by morphological watershed, by voting for the feature point cluster in each region. The labeling result represents the moving object extraction. Experimental results reveal that the proposed method provides extraction results with the suitable object number.