Abstract
Point cloud has been widely used in various fields such as virtual reality and autonomous driving. As the basis of point cloud processing, the research of point cloud classification draw many attentions. This paper proposes a views-based framework for streaming point cloud classification. We obtain six views from coded stream without fully decoding as the inputs of the neural network, and then a modified ResNet structure is proposed to generate the final classification results. The experimental results show that our framework achieve comparable result, while it could be used when the input is streaming point cloud data.
This work is supported by the National Natural Science Foundation of China under Grant Nos. 61971383 and 61631016, and the Fundamental Research Funds for the Central Universities under Grant Nos. 2018XNG1824 and YLSZ180226.
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Li, Q., Ye, L., Zhong, W., Fang, L., Zhang, Q. (2020). Point Cloud Classification via the Views Generated from Coded Streaming Data. In: Zhai, G., Zhou, J., Yang, H., An, P., Yang, X. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2019. Communications in Computer and Information Science, vol 1181. Springer, Singapore. https://doi.org/10.1007/978-981-15-3341-9_31
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DOI: https://doi.org/10.1007/978-981-15-3341-9_31
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