Neural Networks
Computer animation of knowledge-based human grasping
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
IEEE Computer Graphics and Applications
Visual tracking of high DOF articulated structures: an application to human hand tracking
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Active shape models—their training and application
Computer Vision and Image Understanding
Evaluation of the CyberGlove as a whole-hand input device
ACM Transactions on Computer-Human Interaction (TOCHI)
Glove-TalkII: an adaptive gesture-to-formant interface
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Task-Specific Gesture Analysis in Real-Time Using Interpolated Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Model-Based Analysis of Hand Posture
IEEE Computer Graphics and Applications
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Modeling the constraints of human hand motion
HUMO '00 Proceedings of the Workshop on Human Motion (HUMO'00)
Vision based hand modeling and tracking for virtual teleconferencing and telecollaboration
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A neural probabilistic language model
The Journal of Machine Learning Research
Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
BoostMap: a method for efficient approximate similarity rankings
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Neural Networks
Face recognition by applying wavelet subband representation and kernel associative memory
IEEE Transactions on Neural Networks
Review: Ambient intelligence: Technologies, applications, and opportunities
Pervasive and Mobile Computing
Features extraction from hand images based on new detection operators
Pattern Recognition
Attention determination for social robots using salient region detection
ICSR'10 Proceedings of the Second international conference on Social robotics
Enhancing hand gesture recognition using fuzzy clustering-based mixture-of-experts model
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Adaptive mixture-of-experts models for data glove interface with multiple users
Expert Systems with Applications: An International Journal
Hybridization of the probabilistic neural networks with feed-forward neural networks for forecasting
Engineering Applications of Artificial Intelligence
Attention Based Detection and Recognition of Hand Postures Against Complex Backgrounds
International Journal of Computer Vision
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In this paper, we present a computer vision system for human gesture recognition and tracking based on a new nonlinear dimensionality reduction method. Due to the variation of posture appearance, the recognition and tracking of human hand gestures from one single camera remain a difficult problem. We present an unsupervised learning algorithm, distributed locally linear embedding (DLLE), to discover the intrinsic structure of the data, such as neighborhood relationships information. After the embedding of input images are represented in a lower dimensional space, probabilistic neural network (PNN) is employed and a database is set up for static gesture classification. For dynamic gesture tracking, the similarity among the images sequence are utilized. Hand gesture motion can be tracked and dynamically reconstructed according to the image's relative position in the corresponding motion database. The method is robust against the input sequence frames and bad image qualities. Experimental results show that our approach is able to successfully separate different hand postures and track the dynamic gesture.