A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
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Towards Multi-View Object Class Detection
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Learning task-specific similarity
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Robust Object Detection with Interleaved Categorization and Segmentation
International Journal of Computer Vision
The Pascal Visual Object Classes (VOC) Challenge
International Journal of Computer Vision
Accurate, Dense, and Robust Multiview Stereopsis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminative mixture-of-templates for viewpoint classification
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Depth-encoded hough voting for joint object detection and shape recovery
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
LDAHash: Improved Matching with Smaller Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foundations and Trends® in Computer Graphics and Vision
Teaching 3D geometry to deformable part models
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Estimating the aspect layout of object categories
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Viewpoint-aware object detection and pose estimation
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
From contours to 3D object detection and pose estimation
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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We describe an approach to category-level detection and viewpoint estimation for rigid 3D objects from single 2D images. In contrast to many existing methods, we directly integrate 3D reasoning with an appearance-based voting architecture. Our method relies on a nonparametric representation of a joint distribution of shape and appearance of the object class. Our voting method employs a novel parameterization of joint detection and viewpoint hypothesis space, allowing efficient accumulation of evidence. We combine this with a re-scoring and refinement mechanism, using an ensemble of view-specific support vector machines. We evaluate the performance of our approach in detection and pose estimation of cars on a number of benchmark datasets. Finally we introduce the ''Weizmann Cars ViewPoint'' (WCVP) dataset, a benchmark for evaluating continuous pose estimation.