Abstract
In this paper we introduce a representation for object verification and a system for object recognition based on local features, invariant moments, silhouette creation and a ’net’ reduction for depth information. The results are then compared with some of the most recent approaches for object detection such as local features and orientation histograms. Additionally, we used depth information to create descriptors that can be used for 3D verification of detected objects. Moments are computed from a 3D set of points which are arranged to create a descriptive object model. This information showed to be of matter in the decision whether the object is present within the analyzed image segment, or not.
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Jain, R., Kasturi, R., Schunck, B.G.: Machine Vision. McGraw-Hill, Inc. (1995)
Baerveldt, A.J.: A vision system for object verification and localization based on local features. Robotics and Autonomous Systems 34(2-3), 83–92 (2001)
Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (surf). Computer Vision and Image Understanding 110(3), 346–359 (2008)
Cortes, C., Vapnik, V.: Support-vector networks. Machine Learning 20, 273–297 (1995)
Ma, Y., Soatto, S., Kosecka, J., Sastry, S.S.: An Invitation to 3-D Vision: From Images to Geometric Models. Springer (2003)
Hu, M.K.: Visual pattern recognition by moment invariants. IRE Transactions on Information Theory 8(2), 179–187 (1962)
Belkasim, S., Shridhar, M., Ahmadi, M.: Pattern recognition with moment invariants: A comparative study and new results. Pattern Recognition 24(12), 1117–1138 (1991)
Mercimek, M., Gulez, K., Mumcu, T.V.: Real object recognition using moment invariants. Sadhana 30, 765–775 (2005)
Rizon, M., Yazid, H., Saad, P., Yeon, A., Shakaff, M., Saad, A.R.M., Mamat, R., Yacoob, S., Desa, H., Karthigayan, M.: Object detection using geometric invariant moment. American Journal of Applied Sciences 2, 1876–1878 (2006)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 886–893. IEEE Computer Society, Washington, DC (2005)
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Villavicencio, L., Lopez-Franco, C., Arana-Daniel, N., Lopez-Franco, L. (2013). 3D Representation for Object Detection and Verification. In: Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F., Rodríguez, J.S., di Baja, G.S. (eds) Pattern Recognition. MCPR 2013. Lecture Notes in Computer Science, vol 7914. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38989-4_6
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DOI: https://doi.org/10.1007/978-3-642-38989-4_6
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