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Computational Statistics & Data Analysis
CONDENSATION—Conditional Density Propagation forVisual Tracking
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Shock Graphs and Shape Matching
International Journal of Computer Vision
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Perceptual Organization and Visual Recognition
Probabilistic Detection and Tracking of Motion Boundaries
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BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
On the Local Form and Transitions of Symmetry Sets, Medial Axes, and Shocks
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Perceptual Grouping by Selection of a Logically Minimal Model
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
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ICML '05 Proceedings of the 22nd international conference on Machine learning
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ACM SIGGRAPH 2006 Papers
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Globally Optimal Grouping for Symmetric Boundaries
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Matching 2D Shapes using their Symmetry Sets
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Alternative 2D Shape Representations using the Symmetry Set
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Shape Classification Using the Inner-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Groups of Adjacent Contour Segments for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
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International Journal of Computer Vision
Path Similarity Skeleton Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Star Shape Prior for Graph-Cut Image Segmentation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Contour Context Selection for Object Detection: A Set-to-Set Contour Matching Approach
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Medial Representations: Mathematics, Algorithms and Applications
Medial Representations: Mathematics, Algorithms and Applications
DP-SLAM: fast, robust simultaneous localization and mapping without predetermined landmarks
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Object detection combining recognition and segmentation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Object detection by contour segment networks
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Describing and matching 2d shapes by their points of mutual symmetry
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
A boundary-fragment-model for object detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
IEEE Transactions on Robotics
P-SLAM: Simultaneous Localization and Mapping With Environmental-Structure Prediction
IEEE Transactions on Robotics
Skeleton Search: Category-Specific Object Recognition and Segmentation Using a Skeletal Shape Model
International Journal of Computer Vision
On the Local Form and Transitions of Pre-symmetry Sets
Journal of Mathematical Imaging and Vision
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In this paper we present a method for grouping relevant object contours in edge maps by taking advantage of contour-skeleton duality. Regularizing contours and skeletons simultaneously allows us to combine both low level perceptual constraints as well as higher level model constraints in a very effective way. The models are represented using paths in symmetry sets. Skeletons are treated as trajectories of an imaginary virtual robot in a discrete space of "symmetric points" obtained from pairs of edge segments. Boundaries are then defined as the maps obtained by grouping the associated pairs of edge segments along the trajectories. Casting the grouping problem in this manner makes it similar to the problem of Simultaneous Localization and Mapping (SLAM). Hence we adapt the state-of-the-art probabilistic framework namely Rao-Blackwellized particle filtering that has been successfully applied to SLAM. We use the framework to maximize the joint posterior over skeletons and contours.