Integration of Image Acquisition and Surface Estimation for Active Stereo Vision Using Multiple Cues

主动计算机视觉利用了对视觉中心、焦点和视觉系统的控制。 立体聚散度，以生成复杂场景的表面图， 就像人类控制视线方向，透镜 变形和眼睛聚散度。 这笔资金将支持两个 研究生开发实时控制算法， 主动立体测距系统 这项工作的动机是 斯珀林的生物视觉模型，并将增加一个试验台 系统，其中主动视觉的合理技术可以 测试.

Active computer vision exploits control of foveation, focus, and stereo vergence to generate surface maps of complex scenes, in much the same way that humans control gaze direction, lens deformation, and eye vergence. This grant will support two graduate students developing algorithms for real-time control of an active stereo range-mapping system. The work is motivated by Sperling's model of biological vision, and will augment a testbed system in which plausible techniques of active vision may be tested.