Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Putting Objects in Perspective
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Robust Object Tracking by Hierarchical Association of Detection Responses
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Particle filters, a quasi-monte carlo solution for segmentation of coronaries
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Tools for semi-automatic monitoring of industrial workflows
Proceedings of the first ACM international workshop on Analysis and retrieval of tracked events and motion in imagery streams
Recent advances and trends in visual tracking: A review
Neurocomputing
Multi-target tracking in crowded scenes
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
On collaborative people detection and tracking in complex scenarios
Image and Vision Computing
Online learned discriminative part-based appearance models for multi-human tracking
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
To track or to detect? an ensemble framework for optimal selection
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Spatio-Temporal clustering model for multi-object tracking through occlusions
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Multi-target tracking on confidence maps: An application to people tracking
Computer Vision and Image Understanding
Detecting pedestrians on a Movement Feature Space
Pattern Recognition
Multiple human tracking system for unpredictable trajectories
Machine Vision and Applications
Multi-Target Tracking by Online Learning a CRF Model of Appearance and Motion Patterns
International Journal of Computer Vision
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We propose a novel approach to increase the robustness of object detection algorithms in surveillance scenarios. The cascaded confidence filter successively incorporates constraints on the size of the objects, on the preponderance of the background and on the smoothness of trajectories. In fact, the continuous detection confidence scores are analyzed locally to adapt the generic detector to the specific scene. The approach does not learn specific object models, reason about complete trajectories or scene structure, nor use multiple cameras. Therefore, it can serve as preprocessing step to robustify many tracking-by-detection algorithms. Our real-world experiments show significant improvements, especially in the case of partial occlusions, changing backgrounds, and similar distractors.