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13 October 1994 Three-dimensional structure estimation for vision-based robotics
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Using known camera motion to estimate 3D structure of a scene from image sequences is an important task in robot manipulation and navigation. This paper presents a new way to integrate 3D structure of a scene, by tracking and fusing 2D line segment measurements over image sequences. The system is based on a cyclic process. The model structure undergoes a cycle of prediction, matching and updating. The process of tracking, matching and updating is based on Kalman filtering framework. In this work no constraint on camera motion is used and segment tracking is based on estimated structure instead of on traditional features tracking based on image motion heuristics. This approach provides for reliability, accuracy, and computational advantages. Experimental results from a camera mounted on a robot arm are presented to illustrate reliability and accuracy of the approach to integrate 3D structure of a scene.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Naser Prljaca and Hugh McCabe "Three-dimensional structure estimation for vision-based robotics", Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994);

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