Object detection and classification from large-scale cluttered indoor scans

Computer Graphics Forum

Volumn 33, Issue 2, 2014, Pages 11-21

  Mattausch, Oliver ^a   Panozzo, Daniele ^b   Mura, Claudio ^a   Sorkine Hornung, Olga ^b   Pajarola, Renato ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

^b ETH ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL TRANSFORMATIONS; OBJECT-ORIENTED DATABASES;

COMPUTATIONAL COSTS; EUCLIDEAN EMBEDDING; GEOMETRIC TRANSFORMATIONS; MEMORY REQUIREMENTS; PRE-PROCESSING STEP; SHAPE DESCRIPTORS; SIMILARITY MEASURE; SPATIAL CONFIGURATION;

OBJECT DETECTION;

EID: 84901857156     PISSN: 01677055     EISSN: 14678659     Source Type: Journal    
DOI: 10.1111/cgf.12286     Document Type: Article

References (38)

1. [AMCO08], Aiger D., Mitra N.J., Cohen-Or D.,: 4-points congruent sets for robust surface registration. ACM Transactions on Graphics 27, 3 (August 2008), 85: 1-10. 8.
2. [ASbF*12], Arikan M., Schwärzler M., Flöry S., Wimmer M., Maierhofer S.,: O-Snap: Optimization-based snapping for modeling architecture. ACM Transactions on Graphics 32, 1 (2012), 6:1-15. 3.
3. [BBW*09], Bokeloh M., Berner A., Wand M., Seidel H.-P., Schilling A.,: Symmetry detection using feature lines. Computer Graphics Forum 28, 2 (2009), 697-706. 2.
4. [BM12], Boulch A., Marlet R.,: Fast and robust normal estimation for point clouds with sharp features. Computer Graphics Forum 31, 5 (2012), 1765-1774. 4.
5. [BN10], Bariya P., Nishino K.,: Scale-hierarchical 3D object recognition in cluttered scenes. In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (2010), pp. 1657-1664. 2.
6. [CML*12], Ceylan D., Mitra N.J., Li H., Weise T., Pauly M.,: Factored facade acquisition using symmetric line arrangements. Computer Graphics Forum 31, 2 (2012), 671-680. 2.
7. [EKS83], Edelsbrunner H., Kirkpatrick D., Seidel R.,: On the shape of a set of points in the plane. IEEE Transactions on Information Theory 29, 4 (1983), 551-559. 4.
8. [EKSX96], Ester M., Kriegel H.-P., Sander J., Xu X.,: A density-based algorithm for discovering clusters in large spatial databases with noise. In Proceedings International Conference on Knowledge Discovery and Data Mining (KDD) (1996), pp. 226-231. 6.
9. [GF09], Golovinskiy A., Funkhouser T.,: Min-cut based segmentation of point clouds. In Proceedings IEEE International Conference on Computer Vision Workshops (2009), pp. 39-46. 2.
10. [GKF09], Golovinskiy A., Kim V.G., Funkhouser T.A.,: Shape-based recognition of 3d point clouds in urban environments. In Proceedings IEEE International Conference on Computer Vision (2009), pp. 2154-2161. 2.
11. [HHF10], Hedau V., Hoiem D., Forsyth D.,: Thinking inside the box: using appearance models and context based on room geometry. In Proceedings European Conference on Computer Vision (2010), pp. 224-237. 2.
12. [HZG*12], Huang Q.-X., Zhang G.-X., GAO L., Hu S.-M., Butscher A., Guibas L.,: An optimization approach for extracting and encoding consistent maps in a shape collection. ACM Transactions on Graphics 31, 6 (2012), 167:1-11. 10.
13. [JKJ*11], Janoch A., Karayev S., Jia Y., Barron J.T., Fritz M., Saenko K., Darrell T.,: A category-level 3-d object dataset: Putting the kinect to work. In Proceedings IEEE International Conference on Computer Vision Workshops (2011), pp. 1168-1174. 3.
14. [KAJS11], Koppula H.S., Anand A., Joachims T., Saxena A.,: Semantic labeling of 3D point clouds for indoor scenes. In Proceedings Conference on Neural Information Processing Systems (2011), pp. 244-252. 2.
15. [KBWS13], Kerber J., Bokeloh M., Wand M., Seidel H.-P.,: Scalable symmetry detection for urban scenes. Computer Graphics Forum 32, 1 (2013), 3-15. 2, 5.
16. [KLM*13], Kim V.G., Li W., Mitra N.J., Chaudhuri S., Di-Verdi S., Funkhouser T.,: Learning part-based templates from large collections of 3d shapes. ACM Transactions on Graphics 32, 4 (July 2013), 70:1-70:12. 2.
17. [KM11], Kim E., Medioni G.,: Scalable object classification using range images. In Proceedings IEEE Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (2011), pp. 65-72. 2.
18. [KMFF13], Karpathy A., Miller S., Fei-Fei L.,: Object discovery in 3d scenes via shape analysis. In International Conference on Robotics and Automation (ICRA) (2013). 2.
19. [KMYG12], Kim Y.M., Mitra N.J., Yan D.-M., Guibas L.,: Acquiring 3D indoor environments with variability and repetition. ACM Transactions on Graphics 31, 6 (2012), 138:1-11. 1, 2.
20. [LA13], Lafarge F., Alliez P.,: Surface reconstruction through point set structuring. Computer Graphics Forum 32, 2 (2013), 225-234. 3.
21. [LBRF11], LAi K., Bo L., Ren X., Fox D.,: A large-scale hierarchical multi-view rgb-d object dataset. In Proceedings IEEE International Conference on Robotics and Automation (2011), pp. 1817-1824. 3.
22. [LBRF12], Lai K., Bo L., Ren X., Fox D.,: Detection-based object labeling in 3d scenes. In Proceedings IEEE International Conference on Robotics and Automation (2012), pp. 1330-1337. 2.
23. [LCDF10], Lipman Y., Chen X., Daubechies I., Funkhouser T.,: Symmetry factored embedding and distance. ACM Transactions on Graphics 29, 4 (2010), 103:1-12. 6.
24. [LWC*11], Li Y., Wu X., Chrysathou Y., Sharf A., Cohen-Or D., Mitra N.J.,: GlobFit: Consistently fitting primitives by discovering global relations. ACM Transactions on Graphics 30, 4 (2011), 52:1-12. 3.
25. [MGP06], Mitra N.J., Guibas L.J., Pauly M.,: Partial and approximate symmetry detection for 3D geometry. ACM Transactions on Graphics 25, 3 (2006), 560-568. 3.
26. [ML09], Muja M., Lowe D.,: Fast approximate nearest neighbors with automatic algorithm configuration. In Proceedings International Conference on Computer Vision Theory and Application (VISSAPP) (2009), pp. 331-340. 5.
27. [NXS12], Nan L., Xie K., Sharf A.,: A search-classify approach for cluttered indoor scene understanding. ACM Transactions on Graphics 31, 6 (2012), 137:1-10. 1, 2, 8, 9, 10.
28. [NZIS13], Niessner M., Zollhöfer M., Izadi S., Stamminger M.,: Real-time 3d reconstruction at scale using voxel hashing. ACM Transactions on Graphics 32, 6 (2013 November), 169:1-169:11. 8.
29. [OBCS*12], Ovsjanikov M., Ben-Chen M., Solomon J., Butscher A., Guibas L.,: Functional maps: a flexible representation of maps between shapes. ACM Transactions on Graphics 31, 4 (2012), 30:1-11. 10.
30. [PMG*05], Pauly M., Mitra N.J., Giesen J., Gross M., Guibas L.J.,: Example-based 3D scan completion. In Proceedings Eurographics Symposium on Geometry Processing (2005), pp. 23-32. 10.
31. [PMW*08], Pauly M., Mitra N.J., Wallner J., Pottmann H., Guibas L.J.,: Discovering structural regularity in 3D geometry. ACM Transactions on Graphics 27, 3 (2008), 43:1-11. 2.
32. [SF11], Silberman N., Fergus R.,: Indoor scene segmentation using a structured light sensor. In Proceedings IEEE International Conference on Computer Vision Workshops (2011), pp. 601-608. 2.
33. [SHKF12], Silberman N., Hoiem D., Kohli P., Fergus R.,: Indoor segmentation and support inference from rgbd images. In Proceedings European Conference on Computer Vision (2012), pp. 746-760. 3.
34. [STS10], Shin J., Triebel R., Siegwart R.,: Unsupervised discovery of repetitive objects. In Proceedings IEEE International Conference on Robotics and Automation (2010), pp. 5041-5046. 2.
35. [SvKK*11], Sidi O., van Kaick O., Kleiman Y., Zhang H., Cohen-Or D.,: Unsupervised co-segmentation of a set of shapes via descriptor-space spectral clustering. ACM Transactions on Graphics 30, 6 (2011), 126:1-10. 2, 10.
36. [SXZ*12], Shao T., Xu W., Zhou K., Wang J., Li D., Guo B.,: An interactive approach to semantic modeling of indoor scenes with an rgbd camera. ACM Transactions on Graphics 31, 6 (2012), 136:1-11. 1, 2.
37. [TDS10], Tombari F., Di Stefano L.,: Object recognition in 3d scenes with occlusions and clutter by hough voting. In Proceedings Pacific-Rim Symposium on Image and Video Technology (2010), pp. 349-355. 2.
38. [TSS10], Triebel R., Shin J., Siegwart R.,: Segmentation and unsupervised part-based discovery of repetitive objects. In Proceedings Robotics: Science and Systems Conference (2010). 2.