Proceedings Article10.1109/CVPR.1996.517058
Hand segmentation using learning-based prediction and verification for hand sign recognition
Yuntao Cui,John J. Weng +1 more
- 18 Jun 1996
- pp 88-93
81
TL;DR: This paper presents a prediction-and-verification segmentation scheme that can handle a large number of different deformable objects presented in complex backgrounds and is relatively efficient since the segmentation is guided by the past knowledge through a prediction andverification scheme.
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Abstract: This paper presents a prediction-and-verification segmentation scheme wing attention images from multiple fixations. A major advantage of this scheme is that it can handle a large number of different deformable objects presented in complex backgrounds. The scheme is also relatively efficient since the segmentation is guided by the past knowledge through a prediction-and-verification scheme. The system has been tested to segment hands in the sequences of intensity images, where each sequence represents a hand sign. The experimental result showed a 95% correct segmentation rate with a 3% false rejection rate.
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References
Snakes : Active Contour Models
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
•Dissertation
Visual Recognition of American Sign Language Using Hidden Markov Models.
Thad Starner
- 01 Feb 1995
TL;DR: Using hidden Markov models (HMM's), an unobstrusive single view camera system is developed that can recognize hand gestures, namely, a subset of American Sign Language (ASL), achieving high recognition rates for full sentence ASL using only visual cues.
Motion segmentation and qualitative dynamic scene analysis from an image sequence
TL;DR: This article presents a motion-based segmentation method relying on 2-D affine motion models and a statistical regularization approach which ensures stable motion- based partitions and results obtained on several real-image sequences corresponding to complex outdoor situations are reported.
266
A state-based technique for the summarization and recognition of gesture
Aaron F. Bobick,Andrew D. Wilson +1 more
- 20 Jun 1995
TL;DR: This work develops techniques for computing a prototype trajectory of an ensemble of trajectories, for defining configuration states along the prototype, and for recognizing gestures from an unsegmented, continuous stream of sensor data.
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