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1 March 1990 Dynamic Motion Vision
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Proceedings Volume 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques; (1990) https://doi.org/10.1117/12.969789
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States
Abstract
We present a method for the recovery of environment structure and camera motion from a sequence of images taken by a camera in motion. Unlike previous approaches, our method of Dynamic Motion Vision explicitly models the perceived temporal variation of the scene structure in the form of a dynamical system. We use the Kalman Filter algorithm to optimally estimate depth values at every picture cell from optical flow. We interleave a least-squares motion estimation with the stages of the Kalman Filter. Our algorithm can therefore estimate both the structure of a scene and the camera motion simultaneously in an incremental fashion which improves the estimates as new images become available. Results of experiments on synthetic and real images are presented.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joachim Heel "Dynamic Motion Vision", Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); https://doi.org/10.1117/12.969789
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