A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
2D Articulated Body Tracking with Self-occultations Handling
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Fast nonparametric belief propagation for real-time stereo articulated body tracking
Computer Vision and Image Understanding
Integration of Local Image Cues for Probabilistic 2D Pose Recovery
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Pattern Recognition Letters
Mean field approach for tracking similar objects
Computer Vision and Image Understanding
Action-specific motion prior for efficient Bayesian 3D human body tracking
Pattern Recognition
Using Hierarchical Models for 3D Human Body-Part Tracking
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
A Study of Parts-Based Object Class Detection Using Complete Graphs
International Journal of Computer Vision
International Journal of Computer Vision
Gaussian Approximation for Tracking Occluding and Interacting Targets
Journal of Mathematical Imaging and Vision
Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences
EURASIP Journal on Advances in Signal Processing - Image processing and analysis in biomechanics
2D Articulated Pose Tracking Using Particle Filter with Partitioned Sampling and Model Constraints
Journal of Intelligent and Robotic Systems
Bottom-up recognition and parsing of the human body
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Boosted multiple deformable trees for parsing human poses
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
3D Reconstruction of Periodic Motion from a Single View
International Journal of Computer Vision
Dual gait generative models for human motion estimation from a single camera
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Robust Pose Recognition of the Obscured Human Body
International Journal of Computer Vision
Self-occlusion handling for human body motion tracking from 3D ToF image sequence
Proceedings of the 1st international workshop on 3D video processing
We are family: joint pose estimation of multiple persons
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Improved human parsing with a full relational model
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Human action recognition using a dynamic Bayesian action network with 2D part models
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Computer Vision and Image Understanding
Finding human poses in videos using concurrent matching and segmentation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Human pose estimation using exemplars and part based refinement
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
International Journal of Computer Vision
Vision-based user-centric light control for smart environments
Pervasive and Mobile Computing
Detection human motion with heel strikes for surveillance analysis
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Upper Body Detection and Tracking in Extended Signing Sequences
International Journal of Computer Vision
Predicting 3d people from 2d pictures
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Human body pose estimation from still images and video frames
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief Propagation
International Journal of Computer Vision
2D Articulated Human Pose Estimation and Retrieval in (Almost) Unconstrained Still Images
International Journal of Computer Vision
Discriminative Appearance Models for Pictorial Structures
International Journal of Computer Vision
Human context: modeling human-human interactions for monocular 3d pose estimation
AMDO'12 Proceedings of the 7th international conference on Articulated Motion and Deformable Objects
Finding people using scale, rotation and articulation invariant matching
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Context and profile based cascade classifier for efficient people detection and safety care system
Multimedia Tools and Applications
Heel strike detection based on human walking movement for surveillance analysis
Pattern Recognition Letters
Discriminative hierarchical part-based models for human parsing and action recognition
The Journal of Machine Learning Research
Computer Vision and Image Understanding
Fast action recognition using negative space features
Expert Systems with Applications: An International Journal
Driver Pose Estimation Using a Mixture-model Method
Proceedings of the Second International Conference on Innovative Computing and Cloud Computing
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Part-based tree-structured models have been widely used for 2D articulated human pose-estimation. These approaches admit efficient inference algorithms while capturing the important kinematic constraints of the human body as a graphical model. These methods often fail however when multiple body parts fit the same image region resulting in global pose estimates that poorly explain the overall image evidence. Attempts to solve this problem have focused on the use of strong prior models that are limited to learned activities such as walking. We argue that the problem actually lies with the image observations and not with the prior. In particular, image evidence for each body part is estimated independently of other parts without regard to self-occlusion. To address this we introduce occlusion-sensitive local likelihoods that approximate the global image likelihood using per-pixel hidden binary variables that encode the occlusion relationships between parts. This occlusion reasoning introduces interactions between non-adjacent body parts creating loops in the underlying graphical model. We deal with this using an extension of an approximate belief propagation algorithm (PAMPAS). The algorithm recovers the real-valued 2D pose of the body in the presence of occlusions, does not require strong priors over body pose and does a quantitatively better job of explaining image evidence than previous methods.