In this paper, a new technique for object classi cation from silhouettes is presented. Hidden Markov Models are used as a classi cation mechanism. Through a set of experiments, we show the validity of our approach and show its invariance under severe rotation conditions. Also, a comparison with other techniques that use Hidden Markov Models for object classi cation from silhouettes is presented.

Silhouette is one of the most popular and effective internal measures for the evaluation of clustering validity. Simplified Silhouette is a computationally simplified version of Silhouette. However, to date Simplified Silhouette has not been systematically analysed in a specific clustering algorithm. This paper analyses the application of Simplified Silhouette to the evaluation of k-means clust...

This paper proposes a method that tracks, and recognizes people in indoor scenes. Background subtraction and foreground silhouette analysis are used to detect people. The colour of each person’s clothes is used as a distinguishing feature for the purpose of tracking and recognizing people. Clothing colour is extracted using histograms on a luminance and perceptually uniform chrominance colour s...

In this paper, an unsupervised, automatic video human members(human body and parts) tracking algorithm is proposed based on a propabilictic human silhouette detection method and a geometric human silhouette analysis algorithm. First, the human silhouette is estimated using the following scheme : 1) an face detection, and 2) a human body detection based on biometric 2-D templates. Next, the huma...

In this paper we examine the problem of reconstructing a (possibly dynamic) ellipsoid from its (possibly inconsistent) orthogonal silhouette projections. We present a particularly convenient representation of ellipsoids as elements of the vector space of symmetric matrices. The relationship between an ellipsoid and its orthogonal projections in this representation is linear, unlike the standard...