Abstract
In this paper, we propose a new approach for 3D human head model retrieval using a single 2D face view only. In this way, the query can be conveniently specified in the form of a single portrait which is in most cases readily available, instead of a 3D model query which is difficult to construct, or text-based query which in general cannot describe the models adequately. To realize this approach, a mapping between the 2D face views and the 3D models needs to be established. In our case, 3D models are represented with a set of adaptive basis functions, while their corresponding 2D face views are characterized with a set of eigenface basis functions. In this way, a particular model and its associated face view can be identified by two separate set of expansion coefficients. To associate the two, we propose to exploit neural network techniques to identify a mapping. With this 2D-3D mapping, we can thus estimate a set of associated 3D expansion coefficients for the input query to retrieve the relevant models in the database.
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Yeung, P.F., Wong, H.S., Ip, H.H.S. (2004). Content-Based Retrieval of 3D Head Models Using a Single Face View Query. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30542-2_114
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DOI: https://doi.org/10.1007/978-3-540-30542-2_114
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