Dynamic Motion Vision

Joachim Heel

doi:10.1117/12.969789

1 March 1990 Dynamic Motion Vision

Joachim Heel

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.

Citation Download Citation

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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