Object recognition and pose estimation based on 3D planar closed loop boundaries

Industrial parts often have various closed loop boundaries (CLBs) of a convex geometric shape such as bolt holes. CLBs can serve as an effective 3D geometric feature for the recognition and pose estimation of industrial parts. However, an accurate extraction of 3D CLBs from a single shot 3D point cloud has been hampered by the possible CLB self-occlusion from a 3D camera perspective, resulting in CLB data separation. In this paper, we present an approach to solving such a self-occlusion issue for accurately identifying 3D CLBs on a planar surface patch. The proposed approach removes out the effect of self-occlusion by transforming an original single shot 3D point cloud represented with reference to the camera frame into that with reference to a frame z-axis of which is orthogonal to the CLB surface patch. This allows the 3D edge of a CLB to be extracted without data separation. Experimental results show that the proposed method not only enable 3D CLB extraction for the case of an arbitrary camera tilting but also improves the accuracy over a conventional method by 30% even for the case of no camera tilting.

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