Hidden Markov Models for Silhouette Classi cation
نویسندگان
چکیده
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.
منابع مشابه
Hidden Markov models for online classification of single trial EEG data
Hidden Markov models (HMMs) are presented for the online classi®cation of single trial EEG data during imagination of a left or right hand movement. The classi®cation shows an improvement of the online experiment and the temporal determination of minimal classi®cation error compared to linear classi®cation methods.
متن کاملMultiresolution Image Classi cation by Hierarchical Modeling with Two Dimensional Hidden Markov Models
The paper is about a multiresolution hidden Markovmodel (MHMM) for classifying images. Each image is represented by feature vectors, which are statistically dependent as modeled by the underlying state process, a multiscale Markov mesh. Unknowns in the model are estimated by maximum likelihood, in particular by employing the EM algorithm. An image is classi ed by nding the optimal set of states...
متن کاملImage Classification Based on a Multiresolution Two Dimensional Hidden Markov Model
This paper presents an image classi cation algorithm using a multiresolution two dimensional hidden Markov model (HMM). The multiresolution two dimensional hidden Markov model is an extension from the two dimensional hidden Markov model for image classi cation. A classi er estimates model parameters using the EM algorithm. Classi cation is then performed according to the maximum a posteriori pr...
متن کاملAudio-Visual Speaker Veri cation using Continuous Fused HMMs
This paper examines audio-visual speaker veri cation using a novel adaptation of fused hidden Markov models, in comparison to output fusion of individual classi ers in the audio and video modalities. A comparison of both hidden Markov model (HMM) and Gaussian mixture model (GMM) classi ers in both modalities under output fusion shows that the choice of audio classi er is more important than vid...
متن کاملImage Classi cation by a Two Dimensional Hidden Markov Model
For block-based classi cation, an image is divided into blocks and a feature vector is formed for each block by grouping statistics extracted from the block. Conventional block-based classi cation algorithms decide the class of a block by examining only the feature vector of this block and ignoring context information. In order to improve classi cation by context, an algorithm is proposed, whic...
متن کامل