Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Shape recognition via Wasserstein distance
Quarterly of Applied Mathematics
Approximation algorithms
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Low Distortion Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Simultaneous Object Recognition and Segmentation from Single or Multiple Model Views
International Journal of Computer Vision
Convex Quadratic Programming for Object Localization
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Matching by Linear Programming and Successive Convexification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Correspondence Via Graph Matching: Models and Global Optimization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Markov Random Field Modeling in Image Analysis
Markov Random Field Modeling in Image Analysis
Local Histogram Based Segmentation Using the Wasserstein Distance
International Journal of Computer Vision
TurboPixels: Fast Superpixels Using Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Unified Probabilistic Approach to Feature Matching and Object Segmentation
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Finding human poses in videos using concurrent matching and segmentation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Shape-Based Object Detection via Boundary Structure Segmentation
International Journal of Computer Vision
Scale resilient, rotation invariant articulated object matching
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Optimal object matching via convexification and composition
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Hi-index | 0.00 |
Object matching can be achieved by finding the superpixels matched across the image and the object template. It can therefore be used for detecting or labeling the object region. However, the matched superpixels are often sparsely distributed within the image domain, and there could therefore be a significant proportion of incorrectly detected or labeled regions even though there are few outlier matches. Consequently, the labeled regions may be unreliable for locating, extracting or representing the object. To address these problems, we propose to impose label priors that were previously incorporated in segmentation on the object matching. Specifically, in order to label as many regions as possible on the object, we propose to adopt the boundary-weighted smoothness prior. To reduce the singular outlier matches as much as possible, we propose to adopt the minimum description length principle adopted in segmentation. We then linearize the priors and incorporate them in the linear programming (LP) formulation of matching. The above gives rise to a novel general LP model for joint object region matching and labeling. This work extends the scope of conventional LP based object matching. The experimental results show that our method compares favorably to the LP based matching methods for object region labeling on a challenging dataset.