Variation and Likeness in Ambient Artistic Portraiture

Not the norm: Face likeness is not the same as similarity to familiar face prototypes

Face images depicting the same individual can differ substantially from one another. Ecological variation in pose, expression, lighting, and other sources of appearance variability complicates the recognition and matching of unfamiliar faces, but acquired familiarity leads to the ability to cope with these challenges. Among the many ways that face of the same individual can vary, some images are judged to be better likenesses of familiar individuals than others. Simply put, these images look more like the individual under consideration than others. But what does it mean for an image to be a better likeness than another? Does likeness entail typicality, or is it something distinct from this? We examined the relationship between the likeness of face images and the similarity of those images to average images of target individuals using a set of famous faces selected for reciprocal familiarity/unfamiliarity across US and UK participants. We found that though likeness judgments are correlated with similarity-to-prototype judgments made by both familiar and unfamiliar participants, this correlation was smaller than the correlation between similarity judgments made by different participant groups. This implies that while familiarity weakens the relationship between likeness and similarity-to-prototype judgments, it does not change similarity-to-prototype judgments to the same degree.

Analysing Texture in Portraits

This case study is an initial exploration as to whether the depiction of texture in a set of portraits, all portraying the same Sitter, is related to the familiar likeness assessments reported in a companion paper containing a principal component analysis (PCA) of the portraits' depiction of shape. Somewhat unexpectedly, a texture PCA failed to discriminate the high from low likeness portraits, despite experimentation with different pre-processing methods to reduce the portraits' high level of uninformative, image-level texture variability. There were some findings arising from these analyses, and while only indicative at this stage, include that linear histogram matching is effective in reducing variability in portrait brightness; that depicting, and perhaps exaggerating, shading relating to lighting direction may enhance portrait likeness; and, that whether minimised or exaggerated, lighting direction can be portrayed somewhat anomalously. Furthermore, and in agreement with findings from photographs, shape and texture were not found to be independent variables, and shape-free image registration, while very usefully enabling a comparison of closely corresponding pixel coordinate values, could itself be a confounding factor for undertaking a texture PCA with portraits produced under relatively ambient conditions.

Likeness, Familiarity, and the Ambient Portrait Average

This artist-led research project involved 10 visual artists producing 10 ambient portraits and a portrait average of a locally familiar Sitter, and 10 ambient portraits and a portrait average of a less locally familiar Sitter. All were then assessed for likeness by more than 150 members of the general public attending an exhibition during Australia's 2018 National Science Week. The results of this study are that portrait averages can be highly shape accurate and tend to be seen as a good likeness by all viewers. However, the portrait average is not necessarily the best likeness. Extending and validating our previous findings regarding the relationship of likeness, familiarity, and shape accuracy (as measured using geometric morphometrics) in portraiture, unfamiliar viewers favouring shape accurate depictions of a Sitter attained statistical significance. Familiar viewers, however, although also tending to view shape accurate depictions a good to very good likeness, were shown to have a stronger preference for portraits that exaggerate a Sitter's facial distinctiveness, including an exaggeration of their head pose, providing such exaggerations are in approximate proportional agreement.