Abstract
The structure information of indoor scene is necessary for a robot who works in a room. In order to achieve structure of an indoor scene, a slice-guided method of indoor scene structure retrieving is proposed in this paper. We present a slicing based approach that transforms three-dimensional (3D) segmentations into two-dimensional (2D) segmentation and segments different kinds of primitive shapes while keeping the global topology structure of the indoor scene. The global topology structure is represented by a graph. The graph is compared with the given indoor scene template. The matched objects and the topology relation between them are finally presented. Our experiment results show that the proposed method performs well on several typical indoor scenes, even if some data are missing.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Nan, L.L., Xie, K., Sharf, A.: A search-classify approach for cluttered indoor scene understanding. ACM Trans. Graph. 31(6), 1–10 (2012)
Silberman, N., Hoiem, D., Kohli, P., Fergus, R.: Indoor segmentation and support inference from RGBD images. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7576, pp. 746–760. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33715-4_54
Socher, R., Huval, B., Bhat, B., et al.: Convolutional-recursive deep learning for 3D object classification. In: Neural Information Processing Systems Conference and Workshop, NIPS, Nevada, pp. 665–673 (2012)
Xu, K., Huang, H., Shi, Y., et al.: Auto scanning for coupled scene reconstruction and proactive object analysis. ACM Trans. Graph. 34(6), 177 (2015)
Xiong, X.H., Huber, D.: Using context to create semantic 3D models of indoor environments. In: British Machine Vision Conference, BMVC 2010, Aberystwyth, UK, pp. 1–11 (2010)
Anand, A., Koppula, H.S., Joachims, T., et al.: Contextually guided semantic labeling and search for 3D point clouds. Int. J. Robot. Res. 32(1), 19–34 (2011)
Jiang, Y., Koppula, H., Saxena, A.: Hallucinated humans as the hidden context for labeling 3D scenes. In: Computer Vision and Pattern Recognition, pp. 2993–3000, IEEE press, Portland (2013)
Savva, M., Chang, A.X., Hanrahan, P., et al.: SceneGrok: inferring action maps in 3D environments. ACM Trans. Graph. 33(6) (2014)
Zhang, Y., Xu, W., Tong, Y., Zhou, K.: Online structure analysis for real-time indoor scene reconstruction. ACM Trans. Graph. 34(5), 159 (2015)
Wang, J., Xie, Q., Xu, Y., et al.: Cluttered indoor scene modeling via functional part-guided graph matching. Comput. Aided Geom. Des. 43(C), 82–94 (2016)
Hao, W., Wang, Y.H.: Structure-based object detection from scene point clouds. Neurocomputing 191, 148–160 (2016)
Schnabel, R., Wahl, R., Wessel, R., et al.: Shape recognition in 3D point-clouds, vol. 272, no. 1, pp. 512–520. Václav Skala - UNION Agency (2008)
Wang, Y., Wang, L., Hao, W, et al.: A novel slicing-based regularization method for raw point clouds in visible IoT, pp. 1–9 (2000)
Guru, D.S., Shekar, B.H., Nagabhushan, P.: A simple and robust line detection algorithm based on small eigenvalue analysis. Pattern Recogn. Lett. 25(1), 1–13 (2004)
Leordeanu, M., Hebert, M.: Unsupervised learning for graph matching. Int. J. Comput. Vis. 96(1), 28–45 (2012)
Acknowledgement
This study is supported by the National Key Research and Development Program of China No. 2018YFB1004905; the Nature Science Foundation of China under Grant No. 61472319, 61872291, 61871320; and in part by Shaanxi Science Research Plan under Grant No. 2017JQ6023; in part by Scientific Research Program Funded by Shaanxi Provincial Education Department 18JS077.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, L., Wang, Y., Wang, N., Ning, X., Lv, K., Huang, L. (2019). A Slice-Guided Method of Indoor Scene Structure Retrieving. In: El Rhalibi, A., Pan, Z., Jin, H., Ding, D., Navarro-Newball, A., Wang, Y. (eds) E-Learning and Games. Edutainment 2018. Lecture Notes in Computer Science(), vol 11462. Springer, Cham. https://doi.org/10.1007/978-3-030-23712-7_26
Download citation
DOI: https://doi.org/10.1007/978-3-030-23712-7_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23711-0
Online ISBN: 978-3-030-23712-7
eBook Packages: Computer ScienceComputer Science (R0)