The NippleAreola Complex for Criminal Identification In digital and multimedia forensics, identification of child sexual offenders based on digital evidence images is highly challenging due to the fact that the offenderxe2x80x99s face or other obvious characteristics such as tattoos are occluded, covered, or not visible at all. Nevertheless, other naked body parts, e.g., chest are still visible. Some researchers proposed skin marks, skin texture, vein or androgenic hair patterns for criminal and victim identification. There are no available studies of nippleareola complex (NAC) for offender identification. In this paper, we present a study of offender identification based on the NAC, and we present NTUNipplev1 dataset, which contains 2732 images of 428 different male nippleareolae. Popular deep learning and handcrafted recognition methods are evaluated on the provided dataset. The results indicate that the NAC can be a useful characteristic for offender identification.

An Empirical Investigation on the Effect of Shape Exaggeration in Face Sketch to Photo Matching Facial sketch to photo retrieval system has useful application in forensic investigation. The main problem identified in the system is that the sketch and photo are from different modality. In order to address this problem, intramodality and intermodality matching approaches have been introduced by many researchers. However, the proposed methods mostly ignore the effects of shape exaggeration of the facial sketch. In this paper, we attempt to investigate empirically and highlight the importance of considering the shape exaggeration effects in any of the two aforementioned matching approaches. This investigation is limited to the Chinese University of Hong Kong (CUHK) Face Sketch Database (CUFS) and CUHK Face Sketch FERET Database (CUFSF) datasets. The results demonstrate that the shape exaggeration effects may reduce retrieval rate accuracy.