3DPO: A three-dimensional part orientation system
International Journal of Robotics Research
The representation, recognition, and locating of 3-d objects
International Journal of Robotics Research
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Multi-Resolution Surface Description of 3-D Objects by Shape-Adaptive Triangular Meshes
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Regularization-Based 3-D Object Modeling from Multiple Range Images
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
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In this paper we present a framework to recognize objects and to determine their pose from a set of objects in a scene for automatic manipulation (bin picking) using pixel-synchronous range and intensity images. The approach uses three-dimensional object models. The object identification and pose estimation process is structured into three stages. The first stage is the feature collection stage, where the feature detection is performed in an area of interest followed by the hypothesis generation, which tries to form hypotheses from consistent features. The last stage, the hypothesis verification, tries to evaluate the hypotheses by comparing the measured range data to the predicted range data from hypothesis and the model.