Abstract
3D local feature descriptor construction is a very challenging task in the field of 3D model analysis. In this paper, an improved Rotational Projection Statistics (IRoPS) descriptor is proposed. For each feature point, the local coordinate system is firstly built and its neighboring points are normalized. Then the normalized neighboring points are rotated and projected onto three coordinate planes. For each rotation, the distribution matrix is computed and the sub-descriptor can be obtained using the central moment, the Shannon entropy, the mean and variance of local depth values. Finally the IRoPS descriptor is constructed by concatenating all the sub-descriptors into a vector. Compared with the Rotational Projection Statistics (RoPS) descriptor, the IRoPS descriptor includes the local depth information and it has better discriminative power. Extensive experiments are performed to verify the superior performance of the proposed descriptor.
Chapter PDF
Similar content being viewed by others
References
Waran, V., Narayanan, V.: Utility of multimaterial 3D printers in creating models with pathological entities to enhance the training experience of neurosurgeons: Technical note. Journal of Neurosurgery 120(2) (2014)
Wang, M., Gao, Y., Lu, K., Rui, Y.: View-based discriminative probabilistic modeling for 3d object retrieval and recognition. IEEE Transactions on Image Processing 22 (2013)
Ohbuchi, R., Otagni, T., Ibato, M., et al.: Shape similarity search of three-dimensional models using parameterized statistics. In: Proceedings of the Pacific Graphics, pp. 265–274. Beijing, China (2002)
Sundar, H., Silver, D., Gagvani, N., et al.: Skeleton based shape matching and retrieval. In: Shape Modeling International, pp. 130–139. IEEE (2003)
Chen, D.-Y., Tian, X.-P., Shen, Y.-T., et al.: On Visual Similarity Based 3D Model Retrieval. Eurographics V22(3) (2003)
Chua, C., Jarvis, R.: Point signatures: a new representation for 3Dobject recognition. International Journal of Computer Vision 25(1), 63–85 (1997)
Johnson, A.E., Hebert, M.: Using spin images for efficient object recognition in cluttered 3D scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(5), 433–449 (1999)
Mian, A., Bennamoun, M., Owens, R.: Three-dimensional model-based object recognition and segmentation in cluttered scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(10), 1584–1601 (2006)
Guo, Y., Sohel, F., Bennamoun, M., Min, L., Wan, J.: Rotational Projection Statistics for 3D Local surface description and object Recongnition. Int. J. Comput. Vis. 105, 63–86 (2013)
Hetzel, G., Leibe, B., Levi, P., Schiele, B.: 3D object recognition from range images using local feature histograms. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, issue II, p. 394 (2001)
Chen, H., Bhanu, B.: 3D free-form object recognition in range images using local surface patches. Pattern Recognition Letters 28(10), 1252–1262 (2007)
Flint, A., Dick, A., Van den Hengel, A.: Local 3D structure recognition in range images. IET Computer Vision 2(4), 208–217 (2008)
Tombari, F., Salti, S., Di Stefano, L.: Unique signatures of histograms for local surface description. In: European Conference on Computer Vision, pp. 356–369. Crete, Greece (2010)
Okoshi, M.T.: Depth Cues in the Human Visual System, Three-Dimensional Imaging Techniques. Academic Press, New York (1976)
Curless, B., Levoy, M.: A volumetric method for building complex models from range images. In: 23rd Annual Conference on Computer Graphics and Interactive, Techniques, pp. 303–312. New Orleans, LA (1996)
Mian, A.S., Bennamoun, M., Owens, R.: A Novel Representation and Feature Matching Algorithm for Automatic Pairwise Registration of Range Images. International Journal of Computer Vision 66(1), 19–40 (2006)
Mian, A., Bennamoun, M., Owens, R.: 3D Model-based Object Recognition and Segmentation in Cluttered Scenes. IEEE Transactions in Pattern Analysis and Machine Intelligence 28(10), 1584–1601 (2006)
Davis, J., Goadrich, M.: The relationship between precision-recall and ROC curves. In: Proceedings of 23rd International Conference on Machine Learning, Pittsburgh, PA (2006)
Malassiotis, S., Strintzis, M.: Snapshots: A novel local surface descriptor and matching algorithm for robust 3D surface alignment. IEEE Trans. Pattern Anal. Mach. Intell. 29(7), 1285–1290 (2007)
Mian, A., Bennamoun, M., Owens, R.: On the repeatability and quality of keypoints for local feature-based 3D object retrieval from cluttered scenes. Int. J. Comput. Vis. 89(2), 348–361 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zeng, H., Zhang, R., Huang, M. (2015). Improved 3D Local Feature Descriptor Based on Rotational Projection Statistics and Depth Information. In: Zha, H., Chen, X., Wang, L., Miao, Q. (eds) Computer Vision. CCCV 2015. Communications in Computer and Information Science, vol 547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48570-5_14
Download citation
DOI: https://doi.org/10.1007/978-3-662-48570-5_14
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-48569-9
Online ISBN: 978-3-662-48570-5
eBook Packages: Computer ScienceComputer Science (R0)