Real Time 3-D Object Recognition From A Range Or Visible Light Image

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Abstract
This paper presents a solution to the problem of recognition and location estimation of complex three dimensional objects in a robotic workspace. We initially assume 3-D data is available in the form of a range image measured by an active triangulation system. The system was designed to meet three criteria: hardware implementation, optimality and real-time execution speed. The assumptions are that a scene contains several objects which may be at any position and orientation and may be arbitrarily overlapping. Each object consists of planar and slowly curving surfaces. The design criteria lead to an approach distinguished by the use of windows. One system using this approach was designed to meet the optimality criterion. Then simplifying approximations were made to improve speed, while maintaining similar performance. The basic approach to segmentation is to divide the range image into windows, classify each window as a particular surface primitive, and group like windows into surface regions. Segmented surface regions are matched with surfaces in an object model using a simple search constrained by a geometric similarity measure. Finally, we describe another system which uses a similar approach with visible light images of the same type of scene.

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