Perceptions of criminality and remorse are critical for legal decision-making. While faces perceived as criminal are more likely to be selected in police lineups and to receive guilty verdicts, faces perceived as remorseful are more likely to receive less severe punishment recommendations. To identify the information that makes a face appear criminal and/or remorseful, we successfully used two different data-driven computational approaches that led to convergent findings: one relying on the use of computer-generated faces, and the other on photographs of (...) people. In addition to visualising and validating the perceived looks of criminality and remorse, we report correlations with earlier face models of dominance, threat, trustworthiness, masculinity/femininity, and sadness. The new face models of criminal and remorseful appearance contribute to our understanding of perceived criminality and remorse. They can be used to study the effects of perceived criminality and remorse on decision-making; research that can ultimately inform legal policies. (shrink)

Research in the field of computer graphics and vision strives to precisely synthesize any possible human face in a way that it is perceived as a real face and to parametrically describe or analyze any existing human face. This article provides an overview of the theoretical and technical steps taken to get a model of human faces that satisfied two demands for face stimuli for experimental research: full control over the information in faces enabling precise manipulations on the one hand, (...) and high ecological validity of the stimuli, i.e. the ability to generate face stimuli that look very natural, on the other. It presents a new technology that fulfills both conditions. An important advance in the development of computer-generated face stimuli is initiated by the proposal of a theoretical face-space framework for the encoding of faces. (shrink)