Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Real-time tracking of image regions with changes in geometry and illumination
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Framework for Modeling Appearance Change in Image Sequences
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Weighted and Robust Incremental Method for Subspace Learning
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Online Learning of Probabilistic Appearance Manifolds for Video-Based Recognition and Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Appearance Modeling Under Geometric Context
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Differential Tracking based on Spatial-Appearance Model (SAM)
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Covariance Tracking using Model Update Based on Lie Algebra
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Dynamic Appearance Modeling for Human Tracking
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
Robust Visual Tracking Based on an Effective Appearance Model
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Adaptive Object Tracking Based on an Effective Appearance Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
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In this paper, we propose an object tracking framework based on a spatial pyramid heat kernel structural information representation. In the tracking framework, we take advantage of heat kernel structural information (HKSI) matrices to represent object appearance, because HKSI matrices perform well in characterizing the edge flow (or structural) information on the object appearance graph. To further capture the multi-level spatial layout information of the HKSI matrices, a spatial pyramid division strategy is adopted. Then, multi-scale HKSI subspace analysis is applied to each spatial pyramid grid at different levels. As a result, several grid-specific HKSI subspace models are obtained and updated by the incremental PCA algorithm. Based on the multi-scale grid-specific HKSI subspace models, we propose a tracking framework using a particle filter to propagate sample distributions over time. Theoretical analysis and experimental evaluations demonstrate the effectiveness of the proposed tracking framework.