View suggestion for interactive segmentation of indoor scenes
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41095_2017_Article_78.pdf
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52.81 MB
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Checksum (MD5)
7a3f95cb0f1031b9c5ddde3346b005fa
Author(s)
Yang, Sheng
Xu, Jie
Chen, Kang
Fu, Hongbo
Date Issued
March 2017
Journal
Computational Visual Media
Publisher
Tsinghua University Press
Citation
Yang, Sheng, Jie Xu, Kang Chen, and Hongbo Fu. “View Suggestion for Interactive Segmentation of Indoor Scenes.” Computational Visual Media 3, no. 2 (March 15, 2017): 131–146.
Version
Author's final manuscript
Abstract
Point cloud segmentation is a fundamental problem. Due to the complexity of real-world scenes and the limitations of 3D scanners, interactive segmentation is currently the only way to cope with all kinds of point clouds. However, interactively segmenting complex and large-scale scenes is very time-consuming. In this paper, we present a novel interactive system for segmenting point cloud scenes. Our system automatically suggests a series of camera views, in which users can conveniently specify segmentation guidance. In this way, users may focus on specifying segmentation hints instead of manually searching for desirable views of unsegmented objects, thus significantly reducing user effort. To achieve this, we introduce a novel view preference model, which is based on a set of dedicated view attributes, with weights learned from a user study. We also introduce support relations for both graph-cut-based segmentation and finding similar objects. Our experiments show that our segmentation technique helps users quickly segment various types of scenes, outperforming alternative methods.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s41095-017-0078-4
