Towards a methodology for retrieving suspects using 3D facial descriptors

We propose a first investigation towards a methodology for exploiting 3D descriptors in suspect retrieval in the context of crime investigation. In this field, the standard method is to construct a facial composite, based on witness description, by an artist of via software, then search a match for it in legal databases. An alternative or complementary scheme would be to define a system of 3D facial attributes that can fit human verbal face description and use them to annotate face databases. Such framework allows a more efficient search of legal face database and more effective suspect shortlisting. In this paper, we describe some first steps towards that goal, whereby we define some novel 3D face attributes, we analyze their capacity for face categorization though a hieratical clustering analysis. Then we present some experiments, using a cohort of 107 subjects, assessing the extent to which some faces partition based on some of these attributes meets its human-based counterpart. Both the clustering analysis and the experiments results reveal encouraging indicators for this novel proposed scheme.