.png){kind=icon}
返回
3D Object Recognition and Pose Estimation From Point Cloud Using Stably Observed Point Pair Feature
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.2978255.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recognition and pose estimation from 3D free-form objects is a key step for autonomous robotic manipulation. Recently, the point pair features (PPF) voting approach has been shown to be effective for simultaneous object recognition and pose estimation. However, the global model descriptor (e.g., PPF and its variants) that contained some unnecessary point pair features decreases the recognition performance and increases computational efficiency. To address this issue, in this paper, we introduce a novel strategy for building a global model descriptor using stably observed point pairs. The stably observed point pairs are calculated from the partial view point clouds which are rendered by the virtual camera from various viewpoints. The global model descriptor is extracted from the stably observed point pairs and then stored in a hash table. Experiments on several datasets show that our proposed method reduces redundant point pair features and achieves better compromise of speed vs accuracy.
Keyword:
Three-dimensional displays
Feature extraction
Solid modeling
Object recognition
Pose estimation
Observability
Computational modeling
3D object recognition
3D pose estimation
point cloud
point pair feature
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
.png){kind=icon}
Rigid 3D geometry matching for grasping of known objects in cluttered scenes用于在杂乱场景中抓取已知对象的刚性3D几何匹配
OAAI
OAAI分享收藏EUV emission spectra in collisions of multiply charged Sn ions with He and Xe多电荷Sn离子与He和Xe碰撞中的EUV发射光谱
PREAI
分享收藏3D object recognition and pose estimation for random bin-picking using Partition Viewpoint Feature Histograms使用分区视点特征直方图进行3D对象识别和姿态估计，用于随机bin拾取
PREAI
分享收藏
查看更多内容