TY - GEN
T1 - Automated recognition of facial expressions authenticity
AU - Radlak, Krystian
AU - Smolka, Bogdan
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/10/31
Y1 - 2016/10/31
N2 - Recognition of facial expressions authenticity is quite troublesome for humans. Therefore, it is an interesting topic for the computer vision community, as the developed algorithms for facial expressions authenticity estimation may be used as indicators of deception. This paper discusses the state-of the art methods developed for smile veracity estimation and proposes a plan of development and validation of a novel approach to automated discrimination between genuine and posed facial expressions. The proposed fully automated technique is based on the extension of the high-dimensional Local Binary Patterns (LBP) to the spatio-Temporal domain and combines them with the dynamics of facial landmarks movements. The proposed technique will be validated on several existing smile databases and a novel database created with the use of a high speed camera. Finally, the developed framework will be applied for the detection of deception in real life scenarios.
AB - Recognition of facial expressions authenticity is quite troublesome for humans. Therefore, it is an interesting topic for the computer vision community, as the developed algorithms for facial expressions authenticity estimation may be used as indicators of deception. This paper discusses the state-of the art methods developed for smile veracity estimation and proposes a plan of development and validation of a novel approach to automated discrimination between genuine and posed facial expressions. The proposed fully automated technique is based on the extension of the high-dimensional Local Binary Patterns (LBP) to the spatio-Temporal domain and combines them with the dynamics of facial landmarks movements. The proposed technique will be validated on several existing smile databases and a novel database created with the use of a high speed camera. Finally, the developed framework will be applied for the detection of deception in real life scenarios.
KW - Deception detection
KW - Facial expressions recognition
KW - Facial expressions spontaneity
KW - Human-computer interaction
KW - Smile genuineness
UR - https://www.scopus.com/pages/publications/85016619144
U2 - 10.1145/2993148.2997624
DO - 10.1145/2993148.2997624
M3 - Conference contribution
AN - SCOPUS:85016619144
T3 - ICMI 2016 - Proceedings of the 18th ACM International Conference on Multimodal Interaction
SP - 577
EP - 581
BT - ICMI 2016 - Proceedings of the 18th ACM International Conference on Multimodal Interaction
A2 - Pelachaud, Catherine
A2 - Nakano, Yukiko I.
A2 - Nishida, Toyoaki
A2 - Busso, Carlos
A2 - Morency, Louis-Philippe
A2 - Andre, Elisabeth
PB - Association for Computing Machinery, Inc
T2 - 18th ACM International Conference on Multimodal Interaction, ICMI 2016
Y2 - 12 November 2016 through 16 November 2016
ER -