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2022
Conference Paper
Titel
Superquadric Indoor Scene Representation for Orientation and Navigation Tasks
Abstract
The use of rescue robots in endangered buildings avoids risking lives. A scene representation for orientation and navigation purposes that is visually understandable and reduces the storage space is needed. Researchers have proposed recovering primitive shapes from different kinds of 3D data. However, most of them focus on recovering individual objects, not complete scenes. Therefore, we propose a combination of planes, superquadrics, and points to abstract scenes from depth maps.The introduced approach consists of the following steps. First, prominent planes in the input data are detected, and their corresponding points are removed. Second, the remaining points are segmented, and a superquadric or a set of superquadrics is recovered from each segment. Finally, the remaining points, the detected planes, and the recovered superquadrics are used to create a parsimonious representation of the input.This approach also introduces a new objective function to recover superquadrics, which provides better results for this application than the existing objective functions. Additionally, a constraint for recovering superquadrics from depth images is proposed, ensuring results consistent with reality.
Author(s)