Active vision
A review of statistical data association for motion correspondence
International Journal of Computer Vision
Region-based strategies for active contour models
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
A Probabilistic Exclusion Principle for Tracking Multiple Objects
International Journal of Computer Vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Tracking via Level Set PDEs without Motion Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moving Object Tracking in Video
AIPR '00 Proceedings of the 29th Applied Imagery Pattern Recognition Workshop
Markov Random Fields with Efficient Approximations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Regression based Bandwidth Selection for Segmentation using Parzen Windows
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Illumination-Invariant Tracking via Graph Cuts
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Real-Time Tracking Using Level Sets
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Closely Coupled Object Detection and Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Effciently Solving Dynamic Markov Random Fields Using Graph Cuts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Bilayer Segmentation of Live Video
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)
POSECUT: simultaneous segmentation and 3D pose estimation of humans using dynamic graph-cuts
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast occluded object tracking by a robust appearance filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection and segmentation of moving objects in complex scenes
Computer Vision and Image Understanding
Experimental Assessment of Probabilistic Integrated Object Recognition and Tracking Methods
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Multiple hypothesis video segmentation from superpixel flows
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Visual tracking using the Earth Mover's Distance between Gaussian mixtures and Kalman filtering
Image and Vision Computing
People tracking algorithm for human height mounted cameras
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
Visual tracking by adaptive kalman filtering and mean shift
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
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This paper presents a new method to both track and segment multiple objects in videos using min-cut/max-flow optimizations. We introduce objective functions that combine low-level pixel wise measures (color, motion), high-level observations obtained via an independent detection module, motion prediction, and contrast-sensitive contextual regularization. One novelty is that external observations are used without adding any association step. The observations are image regions (pixel sets) that can be provided by any kind of detector. The minimization of appropriate cost functions simultaneously allows "detection-before-track" tracking (track-to-observation assignment and automatic initialization of new tracks) and segmentation of tracked objects. When several tracked objects get mixed up by the detection module (e.g., a single foreground detection mask is obtained for several objects close to each other), a second stage of minimization allows the proper tracking and segmentation of these individual entities despite the confusion of the external detection module.