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Object Categorization from RGB-D Local Features and Bag of Words

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Robot 2015: Second Iberian Robotics Conference

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 418))

Abstract

Object categorization from robot perceptions has become one of the most well-known problems in robotics. How to select proper representations for these perceptions, specially when using RGB-D images, has received a significant attention in the last years. We present in this paper an object categorization approach from RGB-D images. This approach is based on the BoW representation, and it allows to integrate any type of 3D local feature implemented in the Point Cloud Library. The experimentation performed over the challenging RGB-D Object dataset shows how competitive object categorization systems can be developed using this procedure.

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References

  1. Blum, M., Springenberg, J.T., Wülfing, J., Riedmiller, M.: A learned feature descriptor for object recognition in RGB-D data. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 1298–1303. IEEE (2012)

    Google Scholar 

  2. Bo, L., Ren, X., Fox, D.: Depth kernel descriptors for object recognition. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 821–826. IEEE (2011)

    Google Scholar 

  3. Bustos, P., Martínez-Gómez, J., García-Varea, I., Rodríguez-Ruiz, L., Bachiller, P., Calderita, L., Manso, L., Sánchez, A., Bandera, A., Bandera, J.P.: Multimodal interaction with loki. In: Workshop de Agentes Físicos, Madrid-Spain (2013)

    Google Scholar 

  4. Csurka, G., Dance, C.R., Fan, L., Willamowski, J., Bray, C.: Visual categorization with bags of keypoints. In: Workshop on Statistical Learning in Computer Vision, ECCV, pp. 1–22 (2004)

    Google Scholar 

  5. Duchenne, O., Joulin, A., Ponce, J.: A graph-matching kernel for object categorization. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 1792–1799. IEEE (2011)

    Google Scholar 

  6. Fodor, I.K.: A survey of dimension reduction techniques (2002)

    Google Scholar 

  7. Holz, D., Behnke, S.: Fast range image segmentation and smoothing using approximate surface reconstruction and region growing. In: Intelligent Autonomous Systems 12, pp. 61–73. Springer (2013)

    Google Scholar 

  8. Jie, L., Tommasi, T., Caputo, B.: Multiclass transfer learning from unconstrained priors. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 1863–1870. IEEE (2011)

    Google Scholar 

  9. Johnson, A.E., Hebert, M.: Using spin images for efficient object recognition in cluttered 3d scenes. IEEE Trans. Pattern Anal. Mach. Intell. 21(5), 433–449 (1999)

    Article  Google Scholar 

  10. Koppula, H.S., Gupta, R., Saxena, A.: Learning human activities and object affordances from RGB-D videos. The International Journal of Robotics Research 32(8), 951–970 (2013)

    Article  Google Scholar 

  11. Lai, K., Bo, L., Ren, X., Fox, D.: A Large-Scale Hierarchical Multi-View RGB-D Object Dataset. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1817–1824, May 2011

    Google Scholar 

  12. Lai, K., Bo, L., Ren, X., Fox, D.: Detection-based object labeling in 3d scenes. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 1330–1337. IEEE (2012)

    Google Scholar 

  13. Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2169–2178. IEEE (2006)

    Google Scholar 

  14. Lv, X., Jiang, S.Q., Herranz, L., Wang, S.: RGB-D hand-held object recognition based on heterogeneous feature fusion. Journal of Computer Science and Technology 30(2), 340–352 (2015)

    Article  Google Scholar 

  15. Martinez-Gomez, J., Cazorla, M., Garcia-Varea, I., Morell, V.: Vidrilo: The visual and depth robot indoor localization with objects information dataset. The International Journal of Robotics Research (2015)

    Google Scholar 

  16. Martínez-Gómez, J., Gámez, J., García-Varea, I., Matellán, V.: Using genetic algorithms for real-time object detection. In: RoboCup 2009: Robot Soccer World Cup XIII. Lecture Notes in Computer Science, vol. 5949, pp. 215–227. Springer, Heidelberg (2010)

    Google Scholar 

  17. Romero-Garcés, A., Calderita, L.V., Martínez-Gómez, J., Bandera, J.P., Marfil, R., Manso, L.J., Bandera, A., Bustos, P.: Testing a fully autonomous robotic salesman in real scenarios. In: 2015 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 124–130. IEEE (2015)

    Google Scholar 

  18. Rusu, R., Blodow, N., Beetz, M.: Fast point feature histograms (FPFH) for 3d registration. In: IEEE International Conference on Robotics and Automation, ICRA 2009, pp. 3212–3217, May 2009

    Google Scholar 

  19. Rusu, R., Cousins, S.: 3D is here: Point Cloud Library (PCL). In: IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, May 9–13 2011 (2011)

    Google Scholar 

  20. Silberman, N., Hoiem, D., Kohli, P., Fergus, R.: Indoor segmentation and supportinference from rgbd images. In: ECCV (2012)

    Google Scholar 

  21. Sipiran, I., Bustos, B.: Harris 3d: a robust extension of the harris operator for interest point detection on 3d meshes. The Visual Computer 27(11), 963–976 (2011)

    Article  Google Scholar 

  22. Steder, B., Rusu, R.B., Konolige, K., Burgard, W.: Narf: 3d range image features for object recognition. In: Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), vol. 44 (2010)

    Google Scholar 

  23. Tombari, F., Salti, S., Di Stefano, L.: Unique signatures of histograms for local surface description. In: Computer Vision-ECCV 2010, pp. 356–369. Springer (2010)

    Google Scholar 

  24. Tombari, F., Salti, S., Di Stefano, L.: A combined texture-shape descriptor for enhanced 3d feature matching. In: 2011 18th IEEE International Conference on Image Processing (ICIP), pp. 809–812, september 2011

    Google Scholar 

  25. Yang, J., Jiang, Y.G., Hauptmann, A.G., Ngo, C.: Evaluating bag-of-visual-words representations in scene classification. In: Proceedings of the International Workshop on Workshop on Multimedia Information Retrieval, MIR 2007, pp. 197–206. ACM, New York (2007)

    Google Scholar 

  26. Zhang, C., Cheng, J., Liu, J., Pang, J., Liang, C., Huang, Q., Tian, Q.: Object categorization in sub-semantic space. Neurocomputing 142, 248–255 (2014)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Computer System Department, University of Castilla-La Manchas, Ciudad Real, Spain

    Jesus Martínez-Gómez, Ismael García-Varea & Cristina Romero-González

  2. Department of Computer Science and Artificial Intelligence, University of Alicante, P.O. Box 99, 03080, Alicante, Spain

    Jesus Martínez-Gómez & Miguel Cazorla

Authors
  1. Jesus Martínez-Gómez
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  2. Miguel Cazorla
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  3. Ismael García-Varea
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  4. Cristina Romero-González
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Corresponding author

Correspondence to Jesus Martínez-Gómez .

Editor information

Editors and Affiliations

  1. Info Syst Dept;Campus de Azurém, University of Minho, Guimarães, Portugal

    Luís Paulo Reis

  2. Electrical and Computer Engineering Dept, University of Porto, Porto, Portugal

    António Paulo Moreira

  3. Instituto Superior Tecnico - Torre Norte, University of Lisboa, Lisboa, Portugal

    Pedro U. Lima

  4. Engineering Dept., E. Ada Byron, Univ of Zaragoza, Computer & Systems, Zaragoza, Spain

    Luis Montano

  5. Automatic Control and Systems Eng. Dept., University of Malaga, Superior Technical, Málaga, Spain

    Victor Muñoz-Martinez

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Martínez-Gómez, J., Cazorla, M., García-Varea, I., Romero-González, C. (2016). Object Categorization from RGB-D Local Features and Bag of Words. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds) Robot 2015: Second Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-319-27149-1_49

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  • DOI: https://doi.org/10.1007/978-3-319-27149-1_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27148-4

  • Online ISBN: 978-3-319-27149-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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