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» Adaptive Background Mixture Models for Real-Time Tracking
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IROS
2007
IEEE
189views Robotics» more  IROS 2007»
16 years 4 days ago
Person following with a mobile robot using binocular feature-based tracking
Abstract— We present the Binocular Sparse Feature Segmentation (BSFS) algorithm for vision-based person following with a mobile robot. BSFS uses Lucas-Kanade feature detection an...
Zhichao Chen, Stanley T. Birchfield
CVPR
2005
IEEE
15 years 11 months ago
Online Selecting Discriminative Tracking Features Using Particle Filter
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
Jianyu Wang, Xilin Chen, Wen Gao
CVPR
2005
IEEE
16 years 7 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
FGR
2000
IEEE
163views Biometrics» more  FGR 2000»
15 years 10 months ago
Tracking Interacting People
A computer vision system for tracking multiple people in relatively unconstrained environments is described. Trackerformed at three levels of abstraction: regions, people and grou...
Stephen J. McKenna, Sumer Jabri, Zoran Duric, Harr...
BMVC
2010
15 years 3 months ago
On-line Adaption of Class-specific Codebooks for Instance Tracking
Off-line trained class-specific object detectors are designed to detect any instance of the class in a given image or video sequence. In the context of object tracking, however, o...
Juergen Gall, Nima Razavi, Luc J. Van Gool