Image Modeling with Position-Encoding Dynamic Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Feature Hierarchies for Object Classification
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Sharing Visual Features for Multiclass and Multiview Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representing shape with a spatial pyramid kernel
Proceedings of the 6th ACM international conference on Image and video retrieval
A stochastic grammar of images
Foundations and Trends® in Computer Graphics and Vision
Learning structural SVMs with latent variables
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to combine bottom-up and top-down segmentation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Recursive Compositional Models for Vision: Description and Review of Recent Work
Journal of Mathematical Imaging and Vision
Object detection using strongly-supervised deformable part models
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Beyond bounding-boxes: learning object shape by model-driven grouping
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Segmentation over detection by coupled global and local sparse representations
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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This paper presents a new object representation, Active Mask Hierarchies (AMH), for object detection. In this representation, an object is described using a mixture of hierarchical trees where the nodes represent the object and its parts in pyramid form. To account for shape variations at a range of scales, a dictionary of masks with varied shape patterns are attached to the nodes at different layers. The shape masks are "active" in that they enable parts to move with different displacements. The masks in this active hierarchy are associated with histograms of words (HOWs) and oriented gradients (HOGs) to enable rich appearance representation of both structured (eg, cat face) and textured (eg, cat body) image regions. Learning the hierarchical model is a latent SVM problem which can be solved by the incremental concave-convex procedure (iCCCP). The resulting system is comparable with the state-of-the-art methods when evaluated on the challenging public PASCAL 2007 and 2009 datasets.