A VLSI pyramid chip for multiresolution image analysis
International Journal of Computer Vision - Special issue: VLSI for computer vision
Face Recognition System Using Local Autocorrelations and Multiscale Integration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Picture Processing
A probabilistic framework for perceptual grouping of features for human face detection
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Towards 3D hand tracking using a deformable model
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Active agent oriented multimodal interface system
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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We propose a system that simultaneously utilizes the stereo disparity and optical flow information of real-time stereo grayscale multiresolution images for the recognition of objects and gestures in human interactions. For real-time calculation of the disparity and optical flow information of a stereo image, the system first creates pyramid images using a Gaussian filter. The system then determines the disparity and optical flow of a low-density image and extracts attention regions in a high-density image. The three foremost regions are recognized using higher-order local autocorrelation features and linear discriminant analysis. As the recognition method is view based, the system can process the face and hand recognitions simultaneously in real time. The recognition features are independent of parallel translations, so the system can use unstable extractions from stereo depth information. We demonstrate that the system can discriminate the users, monitor the basic movements of the user, smoothly learn an object presented by users, and can communicate with users by hand signs learned in advance.