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Abstract: This study continues our work on using stochastic models for image analysis in the context of video indexing. Pseudo-two dimensional Hidden Markov Models (P2DHMM) were shown to be efficient and flexible tools for performing human face localisation in colour images from video sequences. In this context, little constraints can be applied on face images for their identification in view of indexing. Here, we presenta technique based on P2DHMM for recovering face orientation in colour images... (Update)
Active bibliography (related documents): More All
0.0: A Hidden Markov Model-Based Approach for Face Detection and.. - Nefian (1999) (Correct)
0.0: Content-based Video Retrieval: An overview - Marchand-Maillet (2000) (Correct)
0.0: Robust Computer Vision: Theory and Applications - Sebe, Lew (Correct)
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BibTeX entry: (Update)
@misc{ and-stochastic,
author = "St'ephane Marchand-Maillet And",
title = "Stochastic Models for Face Image Analysis",
url = "citeseer.ist.psu.edu/758260.html" }
Citations (may not include all citations):1362 A tutorial on Hidden Markov Models and selected applications.. (context) - Rabiner - 1989
653 Fundamentals of Speech Recognition (context) - Rabiner, Juang - 1993
41 Parameterisation of a stochastic model for human face identi.. - Samaria, Harter - 1994
34 Keyword spotting in poorly printed documents using Pseudo 2-.. (context) - Kuo, Agazzi - 1994
15 Face recognition using an embedded HMM - Nefian - 1999
1 Joint normalization and recognition of degraded documents im.. (context) - Agazzi, Kuo - 1993
1 Pseudo two-dimensional Hidden Markov Models for face detecti.. (context) - Marchand-Maillet, M'erialdo - 1999
1 Hidden Markov Models for image analysis (context) - Marchand-Maillet, pseudo- - 1999
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