Motion analysis of grammatical processes in a visual-gestural language
Proc. of the ACM SIGGRAPH/SIGART interdisciplinary workshop on Motion: representation and perception
Fundamentals of speech recognition
Fundamentals of speech recognition
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
A State-Based Approach to the Representation and Recognition of Gesture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parameterized modeling and recognition of activities
Computer Vision and Image Understanding
Parametric Hidden Markov Models for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Temporal Classification of Natural Gesture and Application to Video Coding
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Invariant features for 3-D gesture recognition
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Recognition of human body motion using phase space constraints
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Real-Time Self-Calibrating Stereo Person Tracking Using 3-D Shape Estimation from Blob Features
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
An Appearance-Based Representation of Action
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Learning visual behavior for gesture analysis
ISCV '95 Proceedings of the International Symposium on Computer Vision
Understanding people pointing: the Perseus system
ISCV '95 Proceedings of the International Symposium on Computer Vision
Categorization and Learning of Pen Motion Using Hidden Markov Models
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Exploiting prosodic structuring of coverbal gesticulation
Proceedings of the 6th international conference on Multimodal interfaces
Augmented segmentation and visualization for presentation videos
Proceedings of the 13th annual ACM international conference on Multimedia
Improving continuous gesture recognition with spoken prosody
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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Conventional application of hidden Markov models to the task ofrecognizing human gesture may suffer from multiple sources ofsystematic variation in the sensor outputs. We present twoframeworks based on hidden Markov models which are designed tomodel and recognize gestures that vary in systematic ways. In thefirst, the systematic variation is assumed to be communicative innature, and the input gesture is assumed to belong to gesturefamily. The variation across the family is modeled explicityby the parametric hidden Markov model (PHMM). In the secondframework, variation in the signal is overcome by relying on onlinelearning rather than conventional offline, batch learning.