Noise-Resistant Deep Learning for Object Classification in Three-Dimensional Point Clouds Using a Point Pair Descriptor.
IEEE Robotics and Automation Letters(2018)
摘要
Object retrieval and classification in point cloud data are challenged by noise, irregular sampling density, and occlusion. To address this issue, we propose a point pair descriptor that is robust to noise and occlusion and achieves high retrieval accuracy. We further show how the proposed descriptor can be used in a four-dimensional (4-D) convolutional neural network for the task of object classi...
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关键词
Three-dimensional displays,Histograms,Robustness,Neural networks,Euclidean distance,Machine learning,Geometry
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