An exponential growth of the number of plastic surgery treatments specific to face (from the minimally-invasive ones to the real surgical procedures) has characterized the last two decades and it seems likely that this phenomenon, that has social and cultural meanings and implications, could spread even further in the next years as the average cost of these treatments is lowering and the wish for “beautification” is becoming part of the global esthetics sense. For these reasons, face recognition as an established research topic has a new major challenge: delivering methods capable of high recognition accuracy even in case probe and gallery differ by a surgical alteration of face shape. To this aim is of fundamental importance understanding the range and the extent of the modification produced by the various types of treatments or by a combination of them. We present a survey of the state of the art on this topic, starting by an analysis of the diffusion of the facial plastic surgery and describing the key aspects of each of the most statistically relevant treatments available, resumed by a synthetic table. The paper includes a brief description of all the approaches proposed in the field so far to the best of authors' knowledge and a comparison of the performance reported by the existing methods when applied to the most referenced plastic surgery face dataset to date. A critical discussion of the results achieved so far and an insight about the challenges that still have to be addressed concludes this work.

Deceiving faces: When plastic surgery challenges face recognition / Nappi, Michele; Ricciardi, Stefano; Tistarelli, Massimo. - In: IMAGE AND VISION COMPUTING. - ISSN 0262-8856. - 54:(2016), pp. 71-82. [10.1016/j.imavis.2016.08.012]

Deceiving faces: When plastic surgery challenges face recognition

TISTARELLI, Massimo
Membro del Collaboration Group
2016-01-01

Abstract

An exponential growth of the number of plastic surgery treatments specific to face (from the minimally-invasive ones to the real surgical procedures) has characterized the last two decades and it seems likely that this phenomenon, that has social and cultural meanings and implications, could spread even further in the next years as the average cost of these treatments is lowering and the wish for “beautification” is becoming part of the global esthetics sense. For these reasons, face recognition as an established research topic has a new major challenge: delivering methods capable of high recognition accuracy even in case probe and gallery differ by a surgical alteration of face shape. To this aim is of fundamental importance understanding the range and the extent of the modification produced by the various types of treatments or by a combination of them. We present a survey of the state of the art on this topic, starting by an analysis of the diffusion of the facial plastic surgery and describing the key aspects of each of the most statistically relevant treatments available, resumed by a synthetic table. The paper includes a brief description of all the approaches proposed in the field so far to the best of authors' knowledge and a comparison of the performance reported by the existing methods when applied to the most referenced plastic surgery face dataset to date. A critical discussion of the results achieved so far and an insight about the challenges that still have to be addressed concludes this work.
2016
Deceiving faces: When plastic surgery challenges face recognition / Nappi, Michele; Ricciardi, Stefano; Tistarelli, Massimo. - In: IMAGE AND VISION COMPUTING. - ISSN 0262-8856. - 54:(2016), pp. 71-82. [10.1016/j.imavis.2016.08.012]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11388/176832
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