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Visual recognition and pose estimation of 3D industrial objects are challenging due to variations of geometric shapes from perspectives while lacking textures. This paper presents an approach to accurately recognizing industrial objects and estimating their poses based on an adaptive Bayesian framework with optimal feature selection and model-based point cloud matching. First, feature sets that provide...
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