Structure-based Object Classification and Recognition for 3D Scenes in Point Clouds

被引:4
|
作者
Ning Xiaojuan [1 ]
Wang Yinghui [1 ]
Hao Wen [1 ]
Zhao Minghua [1 ]
Sui Liansheng [1 ]
Shi Zhenghao [1 ]
机构
[1] Xian Univ Technol, Inst Comp Sci & Engn, Xian, Peoples R China
基金
中国博士后科学基金; 国家教育部博士点专项基金资助; 中国国家自然科学基金;
关键词
point clouds; object segmentation; object recognition; low-level feature; high-level feature; RECONSTRUCTION;
D O I
10.1109/ICVRV.2014.70
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Scene understanding is a critical issue in the advances of intelligent space. Given a 3D point cloud captured for a static scene by laser scanning, we propose a structure-based scene representation and object recognition method. Our method consists of three steps: (1) the scene is segmented and all of the segmented objects in scanned scene are described respectively by features, including size, location, shape, relationship and constraints between multiple-objects which make it easier to construct the logic representation of geometric and semantic features in scene. (2) Those features are represented by first-order logic and corresponding inference rules are designed to different objects, which could provide prior knowledge for scene understanding and recognition. (3) Then concrete knowledge reasoning rules is used to realize objects recognition including scene structure and details of single objects. Experimental results have shown that our proposed method is simple and effective, and can be applied to different outdoor scenes.
引用
收藏
页码:166 / 173
页数:8
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