Abstract
Craniofacial superimposition involves the process of overlaying a skull with a number of ante-mortem images of an individual and the analysis of their morphological correspondence. This research focused on the skull-face overlay stage with the aim of modeling the expert knowledge that is related to the existing anthropometric differences among landmarks and incorporating it into this stage. Consequently, we have moved from a single-objective optimization problem to a multiobjective optimization one aimed to reduce the distances between pairs of landmarks from each group independently. To tackle it, two classic approaches from the area of multicriteria decision making were used: weighted sum and lexicographical order. The results, which were obtained over a Ground Truth dataset, are promising in those cases where the forensic expert has located a large number of landmarks, and worse results than the state of the art method in cases with few landmarks.
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Acknowledgments
This research was supported by the Spanish Ministerio de Economía y Competividad under NEWSOCO project TIN2015-67661-P, and the Andalusian Dept. of Innovación, Ciencia y Empresa under project TIC2011-7745, including European Development Regional Funds (EDRF). Mr. O. Gomez’s work was supported by Spanish MECD FPU grant FPU14/02380. Dr. Ibañez’s work was supported by Spanish MINECO Juan de la Cierva Fellowship JCI-2012-15359.
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Gómez, O., Ibáñez, O., Cordón, O. (2016). Evolutionary Image Registration in Craniofacial Superimposition: Modeling and Incorporating Expert Knowledge. In: Luaces , O., et al. Advances in Artificial Intelligence. CAEPIA 2016. Lecture Notes in Computer Science(), vol 9868. Springer, Cham. https://doi.org/10.1007/978-3-319-44636-3_33
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DOI: https://doi.org/10.1007/978-3-319-44636-3_33
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