Machine Learning
Machine Learning
Probabilistic Tracking with Exemplars in a Metric Space
International Journal of Computer Vision - Marr Prize Special Issue
Comprehensive Database for Facial Expression Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Real-Time Multi-View Face Detection
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
On-Line Selection of Discriminative Tracking Features
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Locality-sensitive hashing scheme based on p-stable distributions
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Detecting Pedestrians Using Patterns of Motion and Appearance
International Journal of Computer Vision
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
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering 3D Human Body Configurations Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Human Detection Using a Cascade of Histograms of Oriented Gradients
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Keypoint Recognition Using Randomized Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human body pose detection using Bayesian spatio-temporal templates
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Randomized Clustering Forests for Image Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation and Recognition Using Structure from Motion Point Clouds
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving object detection with boosted histograms
Image and Vision Computing
A Single Camera Motion Capture System for Human-Computer Interaction
IEICE - Transactions on Information and Systems
Learning Generative Models for Multi-Activity Body Pose Estimation
International Journal of Computer Vision
Local Boosted Features for Pedestrian Detection
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
HOG-Based Decision Tree for Facial Expression Classification
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
A Study of Parts-Based Object Class Detection Using Complete Graphs
International Journal of Computer Vision
Guest Editorial: State of the Art in Image- and Video-Based Human Pose and Motion Estimation
International Journal of Computer Vision
International Journal of Computer Vision
Coupled Visual and Kinematic Manifold Models for Tracking
International Journal of Computer Vision
Optimization and Filtering for Human Motion Capture
International Journal of Computer Vision
Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A real-time object recognition system on cell broadband engine
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
Multivariate relevance vector machines for tracking
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
A hierarchical system for recognition, tracking and pose estimation
MLMI'04 Proceedings of the First international conference on Machine Learning for Multimodal Interaction
Real-time human pose recognition in parts from single depth images
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Computer Vision and Image Understanding
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This paper addresses human detection and pose estimation from monocular images by formulating it as a classification problem. Our main contribution is a multi-class pose detector that uses the best components of state-of-the-art classifiers including hierarchical trees, cascades of rejectors as well as randomized forests. Given a database of images with corresponding human poses, we define a set of classes by discretizing camera viewpoint and pose space. A bottom-up approach is first followed to build a hierarchical tree by recursively clustering and merging the classes at each level. For each branch of this decision tree, we take advantage of the alignment of training images to build a list of potentially discriminative HOG (Histograms of Orientated Gradients) features. We then select the HOG blocks that show the best rejection performances. We finally grow an ensemble of cascades by randomly sampling one of these HOG-based rejectors at each branch of the tree. The resulting multi-class classifier is then used to scan images in a sliding window scheme. One of the properties of our algorithm is that the randomization can be applied on-line at no extra-cost, therefore classifying each window with a different ensemble of randomized cascades. Our approach, when compared to other pose classifiers, gives fast and efficient detection performances with both fixed and moving cameras. We present results using different publicly available training and testing data sets.