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» Probabilistic Object Tracking Using Multiple Features
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CVPR
2007
IEEE
14 years 11 months ago
Learning Features for Tracking
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
Michael Grabner, Helmut Grabner, Horst Bischof
ICIAP
2005
ACM
14 years 9 months ago
Track Matching by Major Color Histograms Matching and Post-matching Integration
Abstract. In this paper we present a track matching algorithm based on the "major color" histograms matching and the post-matching integration useful for tracking a singl...
Eric Dahai Cheng, Massimo Piccardi
CVPR
2007
IEEE
14 years 11 months ago
Kernel-Based 3D Tracking
We present a computer vision system for robust object tracking in 3D by combining evidence from multiple calibrated cameras. This kernel-based 3D tracker is automatically bootstra...
Ambrish Tyagi, Mark A. Keck, James W. Davis, Geras...
ICCV
2007
IEEE
14 years 3 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
JUCS
2010
265views more  JUCS 2010»
13 years 7 months ago
A General Framework for Multi-Human Tracking using Kalman Filter and Fast Mean Shift Algorithms
: The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human track...
Ahmed Ali, Kenji Terada