CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for recognizing the simultaneous aspects of American sign language
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gesture Modeling and Recognition Using Finite State Machines
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Priors for People Tracking from Small Training Sets
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Conditional Random Fields for Contextual Human Motion Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
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
Gesture recognition with a Time-Of-Flight camera
International Journal of Intelligent Systems Technologies and Applications
Robust Object Tracking by Hierarchical Association of Detection Responses
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Sign Language Spotting with a Threshold Model Based on Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Interactive Image Feature Visualization System for Supporting CBIR Study
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Hand trajectory-based gesture spotting and recognition using HMM
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
3D human pose from silhouettes by relevance vector regression
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Real time hand tracking by combining particle filtering and mean shift
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Robust visual tracking for multiple targets
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Real-time human pose recognition in parts from single depth images
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Learning activity patterns using fuzzy self-organizing neural network
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
Retrieving actions in group contexts
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Computer Methods and Programs in Biomedicine
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Gesture recognition has been an attractive research area for decades. Recently, the video game industry has become the major driving force for the development of advanced gesture control technologies. Conventional video games are controlled via physical devices. In contrast, the emerging trend is using camera-based human computer interface (HCI) to capture human gestures and control game playing directly. This paper presents a novel approach for facilitating the development of gesture control-based video games. A time-of-flight (TOF) camera is adopted to provide both depth and greyscale image sequences. 3D perceptual gesture features are extracted and grouped into a generic gesture representation for target gesture recognition. The game control parameters are derived from the recognised gestures on the fly. This framework includes five key modules: 1) perceptual feature extraction; 2) object tracking by perceptual grouping; 3) representation and modelling; 4) gesture recognition; 5) game control parameter generation. A proof-of-concept dart game is implemented for demonstration and evaluation.