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Detecting Deceptive Behaviours through Facial Cues from Videos: A Systematic Review

Articolo
Data di Pubblicazione:
2023
Abstract:
Interest in detecting deceptive behaviours by various application fields, such as security systems, political debates, advanced intelligent user interfaces, etc., makes automatic deception detection an active research topic. This interest has stimulated the development of many deception-detection methods in the literature in recent years. This work systematically reviews the literature focused on facial cues of deception. The most relevant methods applied in the literature of the last decade have been surveyed and classified according to the main steps of the facial-deception-detection process (video pre-processing, facial feature extraction, and decision making). Moreover, datasets used for the evaluation and future research directions have also been analysed.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
deception detection; facial cues; dataset; feature extraction; decision-making algorithms
Elenco autori:
Grifoni, Patrizia; Ferri, Fernando; D'Ulizia, Arianna; D'Andrea, Alessia
Autori di Ateneo:
D'ANDREA ALESSIA
D'ULIZIA ARIANNA
FERRI FERNANDO
GRIFONI PATRIZIA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/458144
Pubblicato in:
APPLIED SCIENCES
Journal
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