Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Complexity of finding dense subgraphs
Discrete Applied Mathematics
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
Towards Multi-View Object Class Detection
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Contour-Based Object Detection in Range Images
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Multiscale Categorical Object Recognition Using Contour Fragments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning an Alphabet of Shape and Appearance for Multi-Class Object Detection
International Journal of Computer Vision
Editorial: Special issue on 3D representation for object and scene recognition
Computer Vision and Image Understanding
From Images to Shape Models for Object Detection
International Journal of Computer Vision
The Pascal Visual Object Classes (VOC) Challenge
International Journal of Computer Vision
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating multiple model views for object recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Object recognition with hierarchical kernel descriptors
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Maximum weight cliques with mutex constraints for video object segmentation
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes
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 propose an approach for view-invariant object detection directly in 3D with following properties: (i) The detection is based on matching of 3D contours to 3D object models. (ii) The matching is constrained with qualitative spatial relations such as above/below, left/right, and front/back. (iii) In order to ensure that any matching solution satisfies these constraints, we formulate the matching problem as finding maximum weight subgraphs with hard constraints, and utilize a novel inference framework to solve this problem. Given a single view of an RGB-D camera, we obtain 3D contours by "back projecting" 2D contours extracted in the depth map. As our experimental results demonstrate, the proposed approach significantly outperforms the state-of-the-art 2D approaches, in particular, latent SVM object detector, as well as recently proposed approaches for object detection in RGB-D data.