CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Human motion analysis: a review
Computer Vision and Image Understanding
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Motion segmentation and pose recognition with motion history gradients
Machine Vision and Applications - Special issue: IEEE WACV
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Cardboard People: A Parameterized Model of Articulated Image Motion
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Individual recognition from periodic activity using hidden Markov models
HUMO '00 Proceedings of the Workshop on Human Motion (HUMO'00)
Real-time recognition of activity using temporal templates
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
A state-based technique for the summarization and recognition of gesture
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Complex Human Activity Recognition for Monitoring Wide Outdoor Environments
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Recognition of Human Motion From Qualitative Normalised Templates
Journal of Intelligent and Robotic Systems
Recognition and segmentation of 3-d human action using HMM and multi-class adaboost
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Generalized hidden Markov models. I. Theoretical frameworks
IEEE Transactions on Fuzzy Systems
Generalized hidden Markov models. II. Application to handwritten word recognition
IEEE Transactions on Fuzzy Systems
Fuzzy Qualitative Robot Kinematics
IEEE Transactions on Fuzzy Systems
A Fuzzy Qualitative Framework for Connecting Robot Qualitative and Quantitative Representations
IEEE Transactions on Fuzzy Systems
UBIAS --- Type Cognitive Systems for Medical Pattern Interpretation
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Classifying 3D Human Motions by Mixing Fuzzy Gaussian Inference with Genetic Programming
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
A fuzzy qualitative framework for indoor rowing kinematics analysis
WSEAS Transactions on Signal Processing
Anomaly detection over spatiotemporal object using adaptive piecewise model
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Pattern Recognition
Information Sciences: an International Journal
Hi-index | 0.00 |
This paper proposes a fuzzy qualitative approach to vision-based human motion analysis with an emphasis on human motion recognition. It achieves feasible computational cost for human motion recognition by combining fuzzy qualitative robot kinematics with human motion tracking and recognition algorithms. First, a data-quantization process is proposed to relax the computational complexity suffered from visual tracking algorithms. Second, a novel human motion representation, i.e., qualitative normalized template, is developed in terms of the fuzzy qualitative robot kinematics framework to effectively represent human motion. The human skeleton ismodeled as a complex kinematic chain, and its motion is represented by a series of such models in terms of time. Finally, experiment results are provided to demonstrate the effectiveness of the proposed method. An empirical comparison with conventional hidden Markov model (HMM) and fuzzy HMM (FHMM) shows that the proposed approach consistently outperforms both HMMs in human motion recognition.