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Pose estimation of occluded objects with an improved template matching method

Jianhua Su, Zhaozuo Liu, Guowei Yang

Year
2016
Citations
5

Abstract

Picking up objects in arbitrary poses is an important step in manufacturing. However, the occlusion of object will cause the picking process difficult. This paper presents a hierarchical detection method to estimate the pose of the object such as rod and bearing even in occluding. Combining the ellipse detection with the template matching, it is possible to identify the pose of a target object that is not be occluded. The propose method will enable a robot to grasp a non-occluded object and ensure a successful picking. Experiments witness the validity the method.

Keywords

Artificial intelligenceComputer visionComputer scienceGRASPObject (grammar)PoseMatching (statistics)Object detectionTemplate matchingProcess (computing)

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