Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Action Recognition Using Probabilistic Parsing
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Conditional Random Fields for Contextual Human Motion Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Human Action Recognition Using Multi-View Image Sequences Features
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Hidden Conditional Random Fields for Gesture Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Robust Scene Extraction Using Multi-Stream HMMs for Baseball Broadcast
IEICE - Transactions on Information and Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
HMM-Based Action Recognition Using Contour Histograms
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Learning to recognize complex actions using conditional random fields
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Factorial hidden Markov models for gait recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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This paper presents comparative results of applying different architectures of generative classifiers (HMM, FHMM, CHMM, Multi-Stream HMM, Parallel HMM ) and discriminative classifier as Conditional Random Fields (CRFs) in human action sequence recognition. The models are fed with histogram of very informative features such as contours evolution and optical-flow. Motion orientation discrimination has been obtained tiling the bounding box of the subject and extracting features from each tile. We run our experiments on two well-know databases, KTH's database and Weizmann's. The results show that both type of models reach similar score, being the generative model better when used with optical flow features and being the discriminative one better when uses with shape-context features.