系统仿真学报 ›› 2015, Vol. 27 ›› Issue (10): 2239-2245.

• 建模与仿真理论及方法 • 上一篇    下一篇

基于KinectFusion的室内场景平面结构重建

蔡晨贾农1,2, 施逸飞1,2, 徐凯1,2, 党岗1   

  1. 1.国防科学技术大学,长沙 410073;
    2.中科院深圳先进技术研究院可视计算研究中心,深圳 518055
  • 收稿日期:2015-06-14 修回日期:2015-07-23 出版日期:2015-10-08 发布日期:2020-08-07
  • 作者简介:蔡晨贾农(1991-),男,内蒙古呼和浩特,蒙古族,硕士生,研究方向为计算机图形学、三维重建;施逸飞(1991-),男,江西萍乡,博士生,研究方向为计算机图形学、室内场景分析。
  • 基金资助:
    国家自然科学基金(61202333, 61272334)

Planar Structure Reconstruction for Indoor Scenes with KinectFusion

Cai Chenjianong1,2, Shi Yifei1,2, Xu Kai1,2, Dang Gang1   

  1. 1. National University of Defence Technology, Changsha 410073, China;
    2. Visual Computing Center, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China
  • Received:2015-06-14 Revised:2015-07-23 Online:2015-10-08 Published:2020-08-07

摘要: 基于KinectFusion的在线扫描与重建技术极大改进了基于消费级深度摄像机的实时室内场景重建。由于目前多数深度摄像机的深度分辨率的限制,使用KinectFusion扫描获得的三维模型数据的重建质量不能满足要求。特别是对室内场景模型中常见的平面结构。这些平面结构往往可以确定室内环境的主要结构。以基于KinectFusion扫描获得室内场景点云数据为基础,提出了一种新的点云分割方法。该方法可准确识别和提取点云数据中的平面结构,并对其进行三维重建。

关键词: KinectFusion, 平面检测, 三维表面重建, 点云分割

Abstract: Online scanning and reconstruction with KinectFusion has greatly improved real-time reconstruction of indoor scenes with consumer depth camera. However, due to the limitation of depth resolution of current depth cameras, the quality of reconstructed scenes is in general unsatisfactory. This is especially true for planar structures which are commonly seen in indoor scenes and important in defining the major structure of an indoor room. A novel method was proposed for extracting and reconstructing planar structures from point clouds of indoor scenes scanned acquired by KinectFusion.

Key words: KinectFusion, plane detection, 3D surface reconstruction, point cloud segmentation

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