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ICCV
2001
IEEE
14 years 11 months ago
Learning Image Statistics for Bayesian Tracking
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Hedvig Sidenbladh, Michael J. Black
ECCV
2008
Springer
14 years 11 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
ECCV
2006
Springer
14 years 11 months ago
Multivariate Relevance Vector Machines for Tracking
This paper presents a learning based approach to tracking articulated human body motion from a single camera. In order to address the problem of pose ambiguity, a one-to-many mappi...
Arasanathan Thayananthan, Ramanan Navaratnam, Bj&o...
ICPR
2008
IEEE
14 years 10 months ago
Human tracking based on Soft Decision Feature and online real boosting
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
Hironobu Fujiyoshi, Masato Kawade, Shihong Lao, Ta...
ICPR
2006
IEEE
14 years 10 months ago
Multiple Objects Tracking with Multiple Hypotheses Graph Representation
We present a novel multi-object tracking algorithm based on multiple hypotheses about the trajectories of the objects. Our work is inspired by Reid's multiple hypothesis trac...
Alex Yong Sang Chia, Liyuan Li, Weimin Huang