.png){kind=icon}
返回
A robust registration algorithm based on salient object detection
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-022-13194-3.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Point cloud registration plays an important role in 3D computer vision. A challenge in this field is the presence of small salient objects with huge flat backgrounds in point clouds, which may result in poor registration. Despite substantial approaches for point cloud registration have been proposed, few attempts have been made to address this problem. In this paper, we present an approach which fully leverages not only geometric information but also texture information presented by RGB images to tackle with this problem. To mitigate the influence of background, we introduce a superior 2D salient object detection method to highlight the role of the salient objects. The color supported generalized iterative closest points algorithm is the state-of-the-art approach in iterative closest points (ICP) variations, which can efficiently exploit the color information. However, it cannot deal with the mentioned problem. On this basis, we further propose a joint objective to align both salient color points and background points. The registration and reconstruction experiments demonstrate the robustness and accuracy of our method.
Keyword:
Point set registration
Salient object detection
RGB-D images
GICP
期刊
IF:
3
论文数:
2.0W
被引数:
3.5W
机构
引用论文
.png){kind=icon}
Data-processing artefacts in three-dimensional dive path reconstruction from geomagnetic and acceleration data从地磁和加速度数据进行三维潜水路径重建中的数据处理伪像
PREAI
分享收藏Perceptually uniform color spaces for color texture analysis: An empirical evaluation用于颜色纹理分析的感知均匀颜色空间: 经验评估
PREAI
分享收藏
分享收藏
查看更多内容