Finding Trajectories of Feature Points in a Monocular Image Sequence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Active vision
A level set approach for computing solutions to incompressible two-phase flow
Journal of Computational Physics
A fast level set method for propagating interfaces
Journal of Computational Physics
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Prior Shapes in Geometric Active Contours in a Variational Framework
International Journal of Computer Vision
Region Tracking via Level Set PDEs without Motion Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '90 Proceedings of the First European Conference on Computer Vision
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
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
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
Geodesic active regions and level set methods for motion estimation and tracking
Computer Vision and Image Understanding
Towards recognition-based variational segmentation using shape priors and dynamic labeling
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Multiregion level set tracking with transformation invariant shape priors
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Active contours for tracking distributions
IEEE Transactions on Image Processing
Geometrically constrained level set tracking for automotive applications
Proceedings of the 32nd DAGM conference on Pattern recognition
Multiregion level set tracking with transformation invariant shape priors
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
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Tracking of regions and object boundaries in an image sequence is a well studied problem in image processing and computer vision. So far, numerous approaches tracking different features of the objects (contours, regions or points of interest) have been presented. Most of these approaches have problems with robustness. Typical reasons are noisy images, objects with identical features or partial occlusions of the tracked features. In this paper we propose a novel level set based tracking approach, that allows robust tracking on noisy images. Our framework is able to track multiple regions in an image sequence, where a level set function is assigned to every region. For already known or learned objects, transformation invariant shape priors can be added to ensure a robust tracking even under partial occlusions. Furthermore, we introduce a simple decision function to maintain the desired topology for multiple regions. Experimental results demonstrate the method for arbitrary numbers of shape priors. The approach can even handle full occlusions and objects which are temporarily hidden in containers.