Abstract
This paper presents a heuristic approach to 3D object recognition by considering multiple 2D projections (appearances) of the objects of interest. Thus, 3D object identification is interpreted as a conventional Content Based Image Retrieval (CBIR) problem. An arbitrary input image of a given object is treated as a search sample within a database (DB) of a large enough set of images, i.e. appearances from a sufficient number of viewpoints for each object. The CBIR method to access the image DB should be both fast enough and sufficiently noise-tolerant. The method we propose is described over two cases of recognition, namely human faces and hand signs of a given sign-language alphabet. Analogically, the method can also be applied to recognition of a large number of 3D objects of different types. We are briefly covering the data gathering technique, its structuring into a DB of image samples, and the experimental study for the noise-resistance of the applied CBIR method. The latter is used to acknowledge the applicability of the proposed approach.
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Dimov, D., Zlateva, N., Marinov, A. (2009). CBIR over Multiple Projections of 3D Objects. In: Fierrez, J., Ortega-Garcia, J., Esposito, A., Drygajlo, A., Faundez-Zanuy, M. (eds) Biometric ID Management and Multimodal Communication. BioID 2009. Lecture Notes in Computer Science, vol 5707. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04391-8_19
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DOI: https://doi.org/10.1007/978-3-642-04391-8_19
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