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2017 | Supplement | Chapter

Semantic Segmentation of Outdoor Areas Using 3D Moment Invariants and Contextual Cues

Authors : Sven Sickert, Joachim Denzler

Published in: Pattern Recognition

Publisher: Springer International Publishing

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Abstract

In this paper, we propose an approach for the semantic segmentation of a 3D point cloud using local 3D moment invariants and the integration of contextual information. Specifically, we focus on the task of analyzing forestal and urban areas which were recorded by terrestrial LiDAR scanners. We demonstrate how 3D moment invariants can be leveraged as local features and that they are on a par with established descriptors. Furthermore, we show how an iterative learning scheme can increase the overall quality by taking neighborhood relationships between classes into account. Our experiments show that the approach achieves very good results for a variety of tasks including both binary and multi-class settings.

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Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)CrossRefMATH

Engel, J., Schöps, T., Cremers, D.: LSD-SLAM: large-scale direct monocular SLAM. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8690, pp. 834–849. Springer, Cham (2014). doi:10.1007/978-3-319-10605-2_54

Fröhlich, B., Rodner, E., Denzler, J.: Semantic segmentation with millions of features: integrating multiple cues in a combined random forest approach. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds.) ACCV 2012. LNCS, vol. 7724, pp. 218–231. Springer, Heidelberg (2013). doi:10.1007/978-3-642-37331-2_17 CrossRef

Frome, A., Huber, D., Kolluri, R., Bülow, T., Malik, J.: Recognizing objects in range data using regional point descriptors. In: Pajdla, T., Matas, J. (eds.) ECCV 2004. LNCS, vol. 3023, pp. 224–237. Springer, Heidelberg (2004). doi:10.1007/978-3-540-24672-5_18 CrossRef

Hackel, T., Wegner, J.D., Schindler, K.: Contour detection in unstructured 3D point clouds. In: IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1610–1618 (2016)

Hackenberg, J., Spiecker, H., Claders, K., Disney, M., Raumonen, P.: Simpletree - an efficient open source tool to build tree models from TLS clouds. Forests 6(11), 4245–4294 (2015)CrossRef

Krückhans, M.: Ein Detektor für Ornamente auf Gebäudefassaden auf Basis des histogram-of-oriented-gradients- Operators, Master’s thesis. Rheinische Friedrich-Wilhelms-Universitt Bonn (2010)

Lang, D., Friedmann, S., Paulus, D.: Semantic 3D octree maps based on conditional random fields. In: IAPR International Conference on Machine Vision Applications, pp. 185–188 (2013)

Lo, C.H., Don, H.S.: 3-D moment forms: their construction and application to object identification and positioning. IEEE Trans. Pattern Anal. Mach. Intell. 11(10), 1053–1064 (1989)CrossRef

10.

Lu, Y., Rasmussen, C.: Simplified Markov random fields for efficient semantic labeling of 3D point clouds. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2690–2697 (2012)

11.

Montillo, A., Shotton, J., Winn, J., Iglesias, J.E., Metaxas, D., Criminisi, A.: Entangled decision forests and their application for semantic segmentation of CT images. In: Székely, G., Hahn, H.K. (eds.) IPMI 2011. LNCS, vol. 6801, pp. 184–196. Springer, Heidelberg (2011). doi:10.1007/978-3-642-22092-0_16 CrossRef

12.

Munoz, D., Bagnell, J.A., Vandapel, N., Hebert, M.: Contextual classification with functional max-margin Markov networks. In: IEEE International Conference on Computer Vision and Pattern Recognition, pp. 975–982 (2009)

13.

Munoz, D., Vandapel, N., Hebert, M.: Onboard contextual classification of 3-D point clouds with learned high-order Markov random fields. In: IEEE International Conference on Robotics and Automation, pp. 2009–2016 (2009)

14.

Schoeler, M., Papon, J., Wörgötter, F.: Constrained planar cuts - object partitioning for point clouds. In: IEEE International Conference on Computer Vision and Pattern Recognition, pp. 5207–5215 (2015)

15.

Shelhamer, E., Long, J., Darrell, T.: Fully convolutional networks for semantic segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39, 640–651 (2017)CrossRef

16.

Shotton, J., Johnson, M., Cipolla, R.: Semantic texton forests for image categorization and segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)

17.

Tombari, F., Salti, S., Stefano, L.: Unique signatures of histograms for local surface description. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6313, pp. 356–369. Springer, Heidelberg (2010). doi:10.1007/978-3-642-15558-1_26 CrossRef

18.

Tombari, F., Stefano, L.D., Giardino, S.: Online learning for automatic segmentaton of 3D data. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4857–4864 (2011)

19.

Trochta, J., Kru̇ček, M., Král, K.: 3D forest. http://www.3dforest.eu/. Accessed 07 Mar 2017

20.

Trummer, M., Süße, H., Denzler, J.: Coarse registration of 3D surface triangulations based on moment invariants with applications to object alignment and identification. In: IEEE International Conference on Computer Vision, pp. 1273–1279 (2009)

21.

Tu, Z., Bai, X.: Auto-context and its application to high-level vision tasks and 3d brain image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 32(10), 1744–1757 (2010)CrossRef

22.

Weinmann, M., Jutzi, B., Mallet, C.: Feature relevance assessment for the semantic interpretation of 3D point cloud data. In: ISPRS Annals of Photgrammetry, Remote Sensing and Spatial Information Science, vol. II-5/W2, pp. 313–318 (2013)

23.

Xiong, X., Munoz, D., Bagnell, J.A., Hebert, M.: 3-D scene analysis via sequenced prediction over points and regions. In: IEEE International Conference on Robotics and Automation, pp. 2609–2616 (2011)

24.

Xu, D., Li, H.: 3-D surface moment invariants. In: International Conference on Pattern Recognition, pp. 173–176 (2006)

Title: Semantic Segmentation of Outdoor Areas Using 3D Moment Invariants and Contextual Cues
Authors: Sven Sickert
Joachim Denzler
Publisher: Springer International Publishing
Book: Pattern Recognition
Print ISBN: 978-3-319-66708-9

Electronic ISBN: 978-3-319-66709-6

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-3-319-66709-6_14

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