Abstract
The extraction of a representative set of features has always been a challenging research topic in image analysis. This interest is even more important when dealing with 3D images. The huge size of these datasets together with the complexity of the tasks where they are needed demand new approaches to the feature extraction problem. The need of an automatic procedure is specially important in many forensic applications, including the reconstruction of 3D models. In this work we propose a new method to automatically extract a set of relevant features from points clouds acquired by a 3D range scanner. We present our results over five views of five skulls, one of them corresponding to a pathological case.
This work was partially supported by the Spain’s Ministerio de Educación y Ciencia (ref. TIN2006-00829) and by the Andalusian Dpto. de Innovación, Ciencia y Empresa (ref. TIC1619), both including EDRF fundings.
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Ballerini, L., Calisti, M., Cordón, O., Damas, S., Santamaría, J. (2008). Automatic Feature Extraction from 3D Range Images of Skulls. In: Srihari, S.N., Franke, K. (eds) Computational Forensics. IWCF 2008. Lecture Notes in Computer Science, vol 5158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85303-9_6
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DOI: https://doi.org/10.1007/978-3-540-85303-9_6
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