CAD-Based Computer Vision: From CAD Models to Relational Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational strategies for object recognition
ACM Computing Surveys (CSUR)
Model-based object recognition in dense-range images—a review
ACM Computing Surveys (CSUR)
Performance comparison of ten variations on the interpretation-tree matching algorithm
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Localization of a Multi-Articulated 3d Object from a Mobile Multisensor System
The 2nd International Symposium on Experimental Robotics II
Evaluation of calibration and localization methods for visually guided grasping
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 2 - Volume 2
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This paper presents the work currently done at LAAS/CNRS about scene interpretation required for manipulation tasks by a mobile arm. This task is composed of two steps : the approach of the mobile platform along the manipulation site and the grasping itself. The paper focuses on the object recognition and localization : the approach step is performed by a simple laser-based navigation procedure. For the grasping step, we use a CAD model of the object and discuss of the problems linked with such a representation : visibility informations must be added so that recognition and grasping strategies could be selected in a formal way. For the recognition, first matchings concerning discriminant patterns allow to generate a first prediction about the object situation; an optimal verification viewpoint can be computed. From this new camera position, we search for maximal sets of matched image features and model primitives; the best recognition hypothesis is determined by the best score. If no prediction can be determined, the system may switch to other discriminant patterns or move the camera respectfull to the arm and robot constraints.