1 August 1991 Actively controlled multiple-sensor system for feature extraction
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Typical vision systems which attempt to extract features from a visual image of the world for the purposes of object recognition and navigation are limited by the use of a single sensor and no active sensor control capability. To overcome limitations and deficiencies of rigid single sensor systems, more and more researchers are investigating actively controlled, multisensor systems. To address these problems, we have developed a self-calibrating system which uses active multiple sensor control to extract features of moving objects. A key problem in such systems is registering the images, that is, finding correspondences between images from cameras of differing focal lengths, lens characteristics, and positions and orientations. The authors first propose a technique which uses correlation of edge magnitudes for continuously calibrating pan and tilt angles of several different cameras relative to a single camera with a wide angle field of view, which encompasses the views of every other sensor. A simulation of a world of planar surfaces, visual sensors, and a robot platform used to test active control for feature extraction is then described. Motion in the field of view of at least one sensor is used to center the moving object for several sensors, which then extract object features such as color, boundary, and velocity from the appropriate sensors. Results are presented from real cameras and from the simulated world.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael J. Daily and Teresa M. Silberberg "Actively controlled multiple-sensor system for feature extraction", Proc. SPIE 1472, Image Understanding and the Man-Machine Interface III, (1 August 1991); doi: 10.1117/12.46474; https://doi.org/10.1117/12.46474

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