Abstract
This paper presents comprehensive analyses of the differences between posed and spontaneous expressions from visible images. First, geometric and appearance features are extracted from the difference images between apex and onset facial images. Secondly, the differences between the posed and spontaneous facial expressions are analyzed through hypothetical testing methods from three aspects: on overall samples, on samples with different genders, and on samples with different expressions. Thirdly, Bayesian networks (BNs) are used to classify posed versus spontaneous expressions from the same three aspects. Statistical analyses on the NVIE database demonstrate the importance of the geometric and appearance features for discriminating posed and spontaneous expressions. Gender effect exists on the differences between posed and spontaneous expressions. It is easier to distinguish posed happiness from spontaneous happiness than other expressions. Recognition experimental results confirm the observations of statistical analyses in most cases.