Abstract:Objective: The purpose of this study was to investigate the effects of the duration of expressions on the recognition of microexpressions, which are closely related to deception. Methods: In two experiments, participants were briefly (from 20 to 300 ms) shown one of six basic expressions and then were asked to identify the expression. Results: The results showed that the participants' performance in recognition of microexpressions increased with the duration of the expressions, reaching a turning point at 200 ms before levelling off. The results also indicated that practice could improve the participants' performance. Conclusions: The results of this study suggest that the proper upper limit of the duration of microexpressions might be around 1/5 of a second and confirmed that the ability to recognize microexpressions can be enhanced with practice.
Abstract. Micro-expressions are one of the most important behavioral clues for lie and dangerous demeanor detections. However, it is difficult for humans to detect micro-expressions. In this paper, a new approach for automatic microexpression recognition is presented. The system is fully automatic and operates in frame by frame manner. It automatically locates the face and extracts the features by using Gabor filters. GentleSVM is then employed to identify microexpressions. As for spotting, the system obtained 95.83% accuracy. As for recognition, the system showed 85.42% accuracy which was higher than the performance of trained human subjects. To further improve the performance, a more representative training set, a more sophisticated testing bed, and an accurate image alignment method should be focused in future research.
Microexpressions are fleeting facial expressions that are important for judging people’s true emotions. Little is known about the neural mechanisms underlying the recognition of microexpressions (with duration of less than 200 ms) and macroexpressions (with duration of greater than 200 ms). We used an affective priming paradigm in which a picture of a facial expression is the prime and an emotional word is the target, and electroencephalogram (EEG) and event-related potentials (ERPs) to examine neural activities associated with recognizing microexpressions and macroexpressions. The results showed that there were significant main effects of duration and valence for N170/vertex positive potential. The main effect of congruence for N400 is also significant. Further, sLORETA showed that the brain regions responsible for these significant differences included the inferior temporal gyrus and widespread regions of the frontal lobe. Furthermore, the results suggested that the left hemisphere was more involved than the right hemisphere in processing a microexpression. The main effect of duration for the event-related spectral perturbation (ERSP) was significant, and the theta oscillations (4 to 8 Hz) increased in recognizing expressions with a duration of 40 ms compared with 300 ms. Thus, there are different EEG/ERPs neural mechanisms for recognizing microexpressions compared to recognizing macroexpressions.
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