A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Real-time American Sign Language recognition from video using hidden Markov models
ISCV '95 Proceedings of the International Symposium on Computer Vision
Recognition and Interpretation of Parametric Gesture
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Multiscale image segmentation by integrated edge and region detection
IEEE Transactions on Image Processing
Multiobject Behavior Recognition by Event Driven Selective Attention Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Gesture and Posture Estimation by Using Locally Linear Regression
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
Hands Tracking from Frontal View for Vision-Based Gesture Recognition
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Extraction of mid-level semantics from gesture videos using a Bayesian network
International Journal of Intelligent Systems Technologies and Applications
Bayesian filter based behavior recognition in workflows allowing for user feedback
Computer Vision and Image Understanding
Attention Based Detection and Recognition of Hand Postures Against Complex Backgrounds
International Journal of Computer Vision
A top-down event-driven approach for concurrent activity recognition
Multimedia Tools and Applications
| Hi-index | 0.01 |
We present a new method for extracting and classifying motion patterns to recognize hand gestures. First, motion segmentatzon of the image sequence is generated based on a muttiscale transform and attributed graph matching of regions across frames. This produces region correspondences and their affine transformations. Second, color information of motion regions is used to determine skin regions. Third, human head and palm regions are identified based on the shape and size of skin areas in motion. Finally, affine transformations defining a region's motion between successive frames are concatenated to construct the region's motion trajectory. Gestural motion trajectories are then classified by a time-delay neural network trained with backpropagation learning algorithm. Our experimental results show that hand gestures can be recognized well using motion patterns.