International Journal of Computer Vision
Modeling the temporal extent of actions
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Superpixels and supervoxels in an energy optimization framework
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Real-Time Object Segmentation Using a Bag of Features Approach
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Automatic image annotation using multiple grid segmentation
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Logistic Stick-Breaking Process
The Journal of Machine Learning Research
Object class segmentation using reliable regions
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
A compositional exemplar-based model for hair segmentation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
An interactive editing framework for electron microscopy image segmentation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
International Journal of Computer Vision
Object Recognition by Sequential Figure-Ground Ranking
International Journal of Computer Vision
Two-granularity tracking: mediating trajectory and detection graphs for tracking under occlusions
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
On the use of regions for semantic image segmentation
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Knowledge leverage from contours to bounding boxes: a concise approach to annotation
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Using models of objects with deformable parts for joint categorization and segmentation of objects
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Integrating multiple character proposals for robust scene text extraction
Image and Vision Computing
Learning graph laplacian for image segmentation
Transactions on Computational Science XIX
Fusion of 3D-LIDAR and camera data for scene parsing
Journal of Visual Communication and Image Representation
Probabilistic Joint Image Segmentation and Labeling by Figure-Ground Composition
International Journal of Computer Vision
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The joint tasks of object recognition and object segmentation from a single image are complex in their requirement of not only correct classification, but also deciding exactly which pixels belong to the object. Exploring all possible pixel subsets is prohibitively expensive, leading to recent approaches which use unsupervised image segmentation to reduce the size of the configuration space. Image segmentation, however, is known to be unstable, strongly affected by small image perturbations, feature choices, or different segmentation algorithms. This instability has led to advocacy for using multiple segmentations of an image. In this paper, we explore the question of how to best integrate the information from multiple bottom-up segmentations of an image to improve object recognition robustness. By integrating the image partition hypotheses in an intuitive combined top-down and bottom-up recognition approach, we improve object and feature support. We further explore possible extensions of our method and whether they provide improved performance. Results are presented on the MSRC 21-class data set and the Pascal VOC2007 object segmentation challenge.