Abstract
Combining visual shape-capturing and vision-based object manipulation without intermediate manual interaction steps is important for autonomic robotic systems. In this work we introduce the concept of such a vision system closing the chain of shape-capturing, detecting and tracking. Therefore, we combine a laser range sensor for the first two steps and a monocular camera for the tracking step. Convex shaped objects in everyday cluttered and occluded scenes can automatically be re-detected and tracked, which is suitable for automated visual servoing or robotic grasping tasks. The separation of shape and appearance information allows different environmental and illumination conditions for shape-capturing and tracking. The paper describes the framework and its components of visual shape-capturing, fast 3D object detection and robust tracking. Experiments show the feasibility of the concept.
This work is supported by the European project MOVEMENT (IST-2003-511670) and by the Austrian Science Foundation grants S9101-N04 and S9103-N04.
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Schlemmer, M.J., Biegelbauer, G., Vincze, M. (2006). An Integration Concept for Vision-Based Object Handling: Shape-Capture, Detection and Tracking. In: Zheng, N., Jiang, X., Lan, X. (eds) Advances in Machine Vision, Image Processing, and Pattern Analysis. IWICPAS 2006. Lecture Notes in Computer Science, vol 4153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11821045_23
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DOI: https://doi.org/10.1007/11821045_23
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