Abstract
Detection of deceptive facial expressions, including estimating smile genuineness, is an important and challenging research topic that draws increasing attention from the computer vision and pattern recognition community. The state-of-the-art methods require localizing a number of facial landmarks to extract sophisticated facial characteristics. In this paper, we explore how to exploit fast smile intensity detectors to extract temporal features. This allows for real-time discrimination between posed and spontaneous expressions at the early smile onset phase.We report the results of experimental validation, which indicate high competitiveness of our method for the UvA-NEMO benchmark database.
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CITATION STYLE
Kawulok, M., Nalepa, J., Nurzynska, K., & Smolka, B. (2016). In search of truth: Analysis of smile intensity dynamics to detect deception. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10022 LNAI, pp. 325–337). Springer Verlag. https://doi.org/10.1007/978-3-319-47955-2_27
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