Object Segmentation and Classification of Point Cloud

Kanokphan LERTNIPHONPHAN; Satoshi KOMORITA; Kazuyuki TASAKA; Hiromasa YANAGIHARA

doi:10.11485/iteac.2017.0_33B-4

2017

DOI https://doi.org/10.11485/iteac.2017.0_33B-4

会議情報

主催: The Institute of Image Information and Television Engineers

会議名: 映像情報メディア学会2017年年次大会

開催地: 東京理科大学葛飾キャンパス

開催日: 2017/08/30 - 2017/09/01

Object Segmentation and Classification of Point Cloud

*Kanokphan LERTNIPHONPHAN, Satoshi KOMORITA, Kazuyuki TASAKA, Hiromasa YANAGIHARA

著者情報

会議録・要旨集フリー

p. 33B-4-

詳細

抄録

Object segmentation and Classification from Point cloud LiDAR are challenging due to its sparseness and lacking of detailed information. In this work, data association between point cloud and RGB image is used to automatically segment objects, which consist of car, cyclist, and pedestrian, for effective making point cloud dataset.

責任著者(Corresponding author)

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