Active Scene Understanding via Online Semantic Reconstruction

dc.contributor.authorZheng, Lintaoen_US
dc.contributor.authorZhu, Chenyangen_US
dc.contributor.authorZhang, Jiazhaoen_US
dc.contributor.authorZhao, Hangen_US
dc.contributor.authorHuang, Huien_US
dc.contributor.authorNiessner, Matthiasen_US
dc.contributor.authorXu, Kaien_US
dc.contributor.editorLee, Jehee and Theobalt, Christian and Wetzstein, Gordonen_US
dc.date.accessioned2019-10-14T05:06:44Z
dc.date.available2019-10-14T05:06:44Z
dc.date.issued2019
dc.description.abstractWe propose a novel approach to robot-operated active understanding of unknown indoor scenes, based on online RGBD reconstruction with semantic segmentation. In our method, the exploratory robot scanning is both driven by and targeting at the recognition and segmentation of semantic objects from the scene. Our algorithm is built on top of a volumetric depth fusion framework and performs real-time voxel-based semantic labeling over the online reconstructed volume. The robot is guided by an online estimated discrete viewing score field (VSF) parameterized over the 3D space of 2D location and azimuth rotation. VSF stores for each grid the score of the corresponding view, which measures how much it reduces the uncertainty (entropy) of both geometric reconstruction and semantic labeling. Based on VSF, we select the next best views (NBV) as the target for each time step. We then jointly optimize the traverse path and camera trajectory between two adjacent NBVs, through maximizing the integral viewing score (information gain) along path and trajectory. Through extensive evaluation, we show that our method achieves efficient and accurate online scene parsing during exploratory scanning.en_US
dc.description.number7
dc.description.sectionheadersGeometric Modeling
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume38
dc.identifier.doi10.1111/cgf.13820
dc.identifier.issn1467-8659
dc.identifier.pages103-114
dc.identifier.urihttps://doi.org/10.1111/cgf.13820
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13820
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectShape analysis
dc.subjectComputer systems organization
dc.subjectRobotic control
dc.titleActive Scene Understanding via Online Semantic Reconstructionen_US
Files
Collections