Indoor Point Cloud Segmentation for Automatic Object Interpretation
نویسندگان
چکیده
The paper presents an algorithm for the automatic segmentation of point clouds from low cost sensors for object interpretation in indoor environments. This algorithm is considering the possible noisy character of the 3D point clouds and is using an iterative RANSAC approach for the segmentation task. For evaluating the robustness, it is applied on two indoor datasets, acquired with the Google Tango tablet and with the NavVis M3 trolley. The realized evaluation reveals the potential of the two systems for delivering data suitable for automatically interpreting indoor structures.
منابع مشابه
Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images
As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...
متن کاملA multi-scale convolutional neural network for automatic cloud and cloud shadow detection from Gaofen-1 images
The reconstruction of the information contaminated by cloud and cloud shadow is an important step in pre-processing of high-resolution satellite images. The cloud and cloud shadow automatic segmentation could be the first step in the process of reconstructing the information contaminated by cloud and cloud shadow. This stage is a remarkable challenge due to the relatively inefficient performanc...
متن کاملEfficient Organized Point Cloud Segmentation with Connected Components
Segmentation is an important step in many perception tasks, such as object detection and recognition. We present an approach to organized point cloud segmentation and its application to plane segmentation, and euclidean clustering for tabletop object detection. The proposed approach is efficient and enables real-time plane segmentation for VGA resolution RGB-D data. Timing results are provided ...
متن کاملNoise-resistant Unsupervised Object Segmentation in Multi-view Indoor Point Clouds
3D object segmentation in indoor multi-view point clouds (MVPC) is challenged by a high noise level, varying point density and registration artifacts. This severely deteriorates the segmentation performance of state-ofthe-art algorithms in concave and highly-curved point set neighborhoods, because concave regions normally serve as evidence for object boundaries. To address this issue, we derive...
متن کاملThermal 3d Mapping for Object Detection in Dynamic Scenes
The automatic analysis of 3D point clouds has become a crucial task in photogrammetry, remote sensing and computer vision. Whereas modern range cameras simultaneously provide both range and intensity images with high frame rates, other devices can be used to obtain further information which could be quite valuable for tasks such as object detection or scene interpretation. In particular thermal...
متن کامل