Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
Learning to Parse Pictures of People
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Object Localization by Bayesian Correlation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Learning to Detect Objects in Images via a Sparse, Part-Based Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
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
Monocular Human Motion Capture with a Mixture of Regressors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Recovering human body configurations: combining segmentation and recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
3D human pose from silhouettes by relevance vector regression
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
Body-Part Templates for Recovery of 2D Human Poses under Occlusion
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
Fast nonparametric belief propagation for real-time stereo articulated body tracking
Computer Vision and Image Understanding
Recovery of upper body poses in static images based on joints detection
Pattern Recognition Letters
3D Human Pose Estimation from Static Images Using Local Features and Discriminative Learning
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
A fast data collection and augmentation procedure for object recognition
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Silhouette representation and matching for 3D pose discrimination - A comparative study
Image and Vision Computing
Patch-based pose inference with a mixture of density estimators
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Learning generative models for monocular body pose estimation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Efficient object detection using orthogonal NMF descriptor hierarchies
Proceedings of the 32nd DAGM conference on Pattern recognition
A two-stage Bayesian network method for 3D human pose estimation from monocular image sequences
EURASIP Journal on Advances in Signal Processing - Special issue on video analysis for human behavior understanding
3D human pose recovery from image by efficient visual feature selection
Computer Vision and Image Understanding
Estimating human pose from occluded images
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Review article: Max-margin Non-negative Matrix Factorization
Image and Vision Computing
Pose estimation with motionlet LLC coding
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
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Recovering the pose of a person from single images is a challenging problem. This paper discusses a bottom-up approach that uses local image features to estimate human upper body pose from single images in cluttered backgrounds. The method takes the image window with a dense grid of local gradient orientation histograms, followed by non negative matrix factorization to learn a set of bases that correspond to local features on the human body, enabling selective encoding of human-like features in the presence of background clutter. Pose is then recovered by direct regression. This approach allows us to key on gradient patterns such as shoulder contours and bent elbows that are characteristic of humans and carry important pose information, unlike current regressive methods that either use weak limb detectors or require prior segmentation to work. The system is trained on a database of images with labelled poses. We show that it estimates pose with similar performance levels to current example-based methods, but unlike them it works in the presence of natural backgrounds, without any prior segmentation.