Low-resolution face alignment and recognition using mixed-resolution classifiers

A very common case for law enforcement is recognition of suspects from a long distance or in a crowd. This is an important application for low-resolution face recognition (in the authors' case, face region below 40 × 40 pixels in size). Normally, high-resolution images of the suspects are used as references, which will lead to a resolution mismatch of the target and reference images since the target images are usually taken at a long distance and are of low resolution. Most existing methods that are designed to match high-resolution images cannot handle low-resolution probes well. In this study, they propose a novel method especially designed to compare low-resolution images with high-resolution ones, which is based on the log-likelihood ratio (LLR). In addition, they demonstrate the difference in recognition performance between real low-resolution images and images down-sampled from high-resolution ones. Misalignment is one of the most important issues in low-resolution face recognition. Two approaches - matching-score-based registration and extended training of images with various alignments - are introduced to handle the alignment problem. Their experiments on real low-resolution face databases show that their methods outperform the state-of-the-art

Performance of distance-based matching algorithms in 3D facial identification

AbstractFacial image identification is an area of forensic sciences, where an expert provides an opinion on whether or not two or more images depict the same individual. The primary concern for facial image identification is that it must be based on sound scientific principles. The recent extensive development in 3D recording technology, which is presumed to enhance performances of identification tasks, has made essential to question conditions, under which 3D images can yield accurate and reliable results. The present paper explores the effect of mesh resolution, adequacy of selected measures of dissimilarity and number of variables employed to encode identity-specific facial features on a dataset of 528 3D face models sampled from the Fidentis 3D Face Database (N∼2100). In order to match 3D images two quantitative approaches were tested, the first based on closest point-to-point distances computed from registered surface models and the second grounded on Procrustes distances derived from discrete 3D facial points collected manually on textured 3D facial models. The results expressed in terms of rank-1 identification rates, ROC curves and likelihood ratios show that under optimized conditions the tested algorithms have the capacity to provide very accurate and reliable results. The performance of the tested algorithms is, however, highly dependent on mesh resolution and the number of variables employed in the task. The results also show that in addition to numerical measures of dissimilarity, various 3D visualization tools can be of assistance in the decision-making

Neural mechanisms of resistance to peer influence in early adolescence

During the shift from a parent-dependent child to a fully autonomous adult, peers take on a significant role in shaping the adolescent’s behaviour. Peer-derived influences are not always positive, however. Here we explore neural correlates of inter-individual differences in the probability of resisting peer influence in early adolescence. Using functional magnetic-resonance imaging (fMRI), we found striking differences between 10-year old children with high and low resistance to peer influence in their brain activity during observation of angry hand-movements and angry facial expressions: compared with subjects with low resistance to peer influence, individuals with high resistance showed a highly coordinated brain activity in neural systems underlying perception of action and decision making. These findings suggest that the probability of resisting peer influence depends on neural interactions during observation of emotion-laden actions

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Neuronal response sto face-like and facial stimuli in the monkey superior colliculus

The superficial layers of the superior colliculus (sSC) appear to function as a subcortical visual pathway that bypasses the striate cortex for the rapid processing of coarse facial information. We investigated the responses of neurons in the monkey sSC during a delayed non-matching-to-sample (DNMS) task in which monkeys were required to discriminate among five categories of visual stimuli [photos of faces with different gaze directions, line drawings of faces, face-like patterns (three dark blobs on a bright oval), eye-like patterns, and simple geometric patterns]. Of the 605 sSC neurons recorded, 216 neurons responded to the visual stimuli. Among the stimuli, face-like patterns elicited responses with the shortest latencies. Low-pass filtering of the images did not influence the responses. However, scrambling of the images increased the responses in the late phase, and this was consistent with a feedback influence from upstream areas. A multidimensional scaling (MDS) analysis of the population data indicated that the sSC neurons could separately encode face-like patterns during the first 25-ms period after stimulus onset, and stimulus categorization developed in the next three 25-ms periods. The amount of stimulus information conveyed by the sSC neurons and the number of stimulus-differentiating neurons were consistently higher during the 2nd to 4th 25-ms periods than during the first 25-ms period. These results suggested that population activity of the sSC neurons preferentially filtered face-like patterns with short latencies to allow for the rapid processing of coarse facial information and developed categorization of the stimuli in later phases through feedback from upstream areas