Active shape models—their training and application
Computer Vision and Image Understanding
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line Selection of Discriminative Tracking Features
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A General Framework for Combining Visual Trackers --- The "Black Boxes" Approach
International Journal of Computer Vision
Robust Fragments-based Tracking using the Integral Histogram
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
ACM Computing Surveys (CSUR)
Multicamera People Tracking with a Probabilistic Occupancy Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Spatial Context: Using Stuff to Find Things
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Semi-supervised On-Line Boosting for Robust Tracking
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Taking the bite out of automated naming of characters in TV video
Image and Vision Computing
Object segmentation by long term analysis of point trajectories
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Feature harvesting for tracking-by-detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Context tracker: Exploring supporters and distracters in unconstrained environments
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Hough-based tracking of non-rigid objects
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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A fundamental problem of object tracking is to adapt to unseen views of the object while not getting distracted by other objects. We introduce Dynamic Objectness in a discriminative tracking framework to sporadically re-discover the tracked object based on motion. In doing so, drifting is effectively limited since tracking becomes more aware of objects as independently moving entities in the scene. The approach not only follows the object, but also the background to not easily adapt to other distracting objects. Finally, an appearance model of the object is incrementally built for an eventual re-detection after a partial or full occlusion. We evaluated it on several well-known tracking sequences and demonstrate results with superior accuracy, especially in difficult sequences with changing aspect ratios, varying scale, partial occlusion and non-rigid objects.