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ICCV
2003
IEEE
14 years 11 months ago
On-Line Selection of Discriminative Tracking Features
This paper presents a method for evaluating multiple feature spaces while tracking, and for adjusting the set of features used to improve tracking performance. Our hypothesis is t...
Robert T. Collins, Yanxi Liu
ICIP
2007
IEEE
14 years 3 months ago
Mean-Shift Blob Tracking with Adaptive Feature Selection and Scale Adaptation
When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we prop...
Dawei Liang, Qingming Huang, Shuqiang Jiang, Hongx...
TCSV
2008
202views more  TCSV 2008»
13 years 9 months ago
Probabilistic Object Tracking With Dynamic Attributed Relational Feature Graph
Object tracking is one of the fundamental problems in computer vision and has received considerable attention in the past two decades. The success of a tracking algorithm relies on...
Feng Tang, Hai Tao
VIS
2007
IEEE
113views Visualization» more  VIS 2007»
14 years 10 months ago
Texture-based Feature Tracking for Effective Time-varying Data Visualization
Analyzing, visualizing, and illustrating changes within time-varying volumetric data is challenging due to the dynamic changes occurring between timesteps. The changes and variatio...
Jesus Caban, Alark Joshi, Penny Rheingans
VIP
2003
13 years 10 months ago
Tracking Using CamShift Algorithm and Multiple Quantized Feature Spaces
The Continuously Adaptive Mean Shift Algorithm (CamShift) is an adaptation of the Mean Shift algorithm for object tracking that is intended as a step towards head and face trackin...
John G. Allen, Richard Y. D. Xu, Jesse S. Jin