Detecting and tracking human face and eye using an space-varying sensor and an active vision head
Abstract
We have developed a system for detecting and tracking human face and eye in an unstructured environment. We adopt a biologically plausible retinally connected neural network architecture and integrate it with an active vision system. While the active vision system tracks the object moving in real-time and the neural network detects the face and eye location from the video stream at a slower rate. This paper provides a systematic way of creating and selecting examples for training the network by exploring the link between theory and practice. Experimental results on real sequence of images from a space-varying sensor depicts the performance of the system.
Publication Title
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Recommended Citation
Yeasin, M., & Kuniyoshi, Y. (2000). Detecting and tracking human face and eye using an space-varying sensor and an active vision head. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 168-173. https://doi.org/10.1109/CVPR.2000.854770
