Tracking and data association
Merging and Splitting Eigenspace Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Data Association Methods for Tracking Complex Visual Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental Singular Value Decomposition of Uncertain Data with Missing Values
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Probabilistic visual learning for object detection
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
On-Line Selection of Discriminative Tracking Features
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Tracking multiple humans in crowded environment
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A Rao-Blackwellized particle filter for EigenTracking
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
PAMPAS: real-valued graphical models for computer vision
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Karhunen-Loeve basis extraction and its application to images
IEEE Transactions on Image Processing
State-of-the-art on spatio-temporal information-based video retrieval
Pattern Recognition
An Active Classification System for Context Representation and Acquisition
Proceedings of the 2007 conference on Advances in Ambient Intelligence
CDL: an Integrated Framework for Context Specification and Recognition
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
IEEE Transactions on Multimedia - Special issue on integration of context and content
Learning scene context for multiple object tracking
IEEE Transactions on Image Processing
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Detection and tracking of large number of targets in wide area surveillance
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Occlusion handling with l1-regularized sparse reconstruction
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Facial expressions in American sign language: Tracking and recognition
Pattern Recognition
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In multitarget tracking, the main challenge is to maintain the correct identity of targets even under occlusions or when differences between the targets are small. The paper proposes a new approach to this problem by incorporating the context information. The context of a target in an image sequence has two components: the spatial context including the local background and nearby targets and the temporal context including all appearances of the targets that have been seen previously. The paper considers both aspects. We propose a new model for multitarget tracking based on the classification of each target against its spatial context. The tracker searches a region similar to the target while avoiding nearby targets. The temporal context is included by integrating the entire history of target appearance based on probabilistic principal component analysis (PPCA). We have developed a newincremental scheme that can learn the full set of PPCA parameters accurately online. The experiments show robust tracking performance under the condition of severe clutter, occlusions, and pose changes.