Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition

This paper presents a robust and dynamic face recognition technique based on the extraction and matching of devised probabilistic graphs drawn on SIFT features related to independent face areas. The face matching strategy is based on matching individual salient facial graph characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster-Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in case of partially occluded faces.Comment: 8 pages, 2 figure

Face image matching using fractal dimension

A new method is presented in this paper for calculating the correspondence between two face images on a pixel by pixel basis. The concept of fractal dimension is used to develop the proposed non-parametric area-based image matching method which achieves a higher proportion of matched pixels for face images than some well-known methods

Matching novel face and voice identity using static and dynamic facial images

Research investigating whether faces and voices share common source identity information has offered contradictory results. Accurate face-voice matching is consistently above chance when the facial stimuli are dynamic, but not when the facial stimuli are static. We tested whether procedural differences might help to account for the previous inconsistencies. In Experiment 1, participants completed a sequential two-alternative forced choice matching task. They either heard a voice and then saw two faces or saw a face and then heard two voices. Face – voice matching was above chance when the facial stimuli were dynamic and articulating, but not when they were static. In Experiment 2, we tested whether matching was more accurate when faces and voices were presented simultaneously. The participants saw two face–voice combinations, presented one after the other. They had to decide which combination was the same identity. As in Experiment 1, only dynamic face–voice matching was above chance. In Experiment 3, participants heard a voice and then saw two static faces presented simultaneously. With this procedure, static face–voice matching was above chance. The overall results, analyzed using multilevel modeling, showed that voices and dynamic articulating faces, as well as voices and static faces, share concordant source identity information. It seems, therefore, that above-chance static face–voice matching is sensitive to the experimental procedure employed. In addition, the inconsistencies in previous research might depend on the specific stimulus sets used; our multilevel modeling analyses show that some people look and sound more similar than others

Training methods for facial image comparison: a literature review

This literature review was commissioned to explore the psychological literature relating to facial image comparison with a particular emphasis on whether individuals can be trained to improve performance on this task. Surprisingly few studies have addressed this question directly. As a consequence, this review has been extended to cover training of face recognition and training of different kinds of perceptual comparisons where we are of the opinion that the methodologies or findings of such studies are informative. The majority of studies of face processing have examined face recognition, which relies heavily on memory. This may be memory for a face that was learned recently (e.g. minutes or hours previously) or for a face learned longer ago, perhaps after many exposures (e.g. friends, family members, celebrities). Successful face recognition, irrespective of the type of face, relies on the ability to retrieve the to-berecognised face from long-term memory. This memory is then compared to the physically present image to reach a recognition decision. In contrast, in face matching task two physical representations of a face (live, photographs, movies) are compared and so long-term memory is not involved. Because the comparison is between two present stimuli rather than between a present stimulus and a memory, one might expect that face matching, even if not an easy task, would be easier to do and easier to learn than face recognition. In support of this, there is evidence that judgment tasks where a presented stimulus must be judged by a remembered standard are generally more cognitively demanding than judgments that require comparing two presented stimuli Davies & Parasuraman, 1982; Parasuraman & Davies, 1977; Warm and Dember, 1998). Is there enough overlap between face recognition and matching that it is useful to look at the literature recognition? No study has directly compared face recognition and face matching, so we turn to research in which people decided whether two non-face stimuli were the same or different. In these studies, accuracy of comparison is not always better when the comparator is present than when it is remembered. Further, all perceptual factors that were found to affect comparisons of simultaneously presented objects also affected comparisons of successively presented objects in qualitatively the same way. Those studies involved judgments about colour (Newhall, Burnham & Clark, 1957; Romero, Hita & Del Barco, 1986), and shape (Larsen, McIlhagga & Bundesen, 1999; Lawson, Bülthoff & Dumbell, 2003; Quinlan, 1995). Although one must be cautious in generalising from studies of object processing to studies of face processing (see, e.g., section comparing face processing to object processing), from these kinds of studies there is no evidence to suggest that there are qualitative differences in the perceptual aspects of how recognition and matching are done. As a result, this review will include studies of face recognition skill as well as face matching skill. The distinction between face recognition involving memory and face matching not involving memory is clouded in many recognition studies which require observers to decide which of many presented faces matches a remembered face (e.g., eyewitness studies). And of course there are other forensic face-matching tasks that will require comparison to both presented and remembered comparators (e.g., deciding whether any person in a video showing a crowd is the target person). For this reason, too, we choose to include studies of face recognition as well as face matching in our revie

Age-dependent differences in human brain activity using a face- and location-matching task: An fMRI study

Purpose: To evaluate the differences of cortical activation patterns in young and elderly healthy subjects for object and spatial visual processing using a face- and location-matching task. Materials and Methods: We performed a face- and a location-matching task in 15 young (mean age: 28 +/- 9 years) and 19 elderly (mean age: 71 +/- 6 years) subjects. Each experiment consisted of 7 blocks alternating between activation and control condition. For face matching, the subjects had to indicate whether two displayed faces were identical or different. For location matching, the subjects had to press a button whenever two objects had an identical position. For control condition, we used a perception task with abstract images. Functional imaging was performed on a 1.5-tesla scanner using an EPI sequence. Results: In the face-matching task, the young subjects showed bilateral (right 1 left) activation in the occipito-temporal pathway (occipital gyrus, inferior and middle temporal gyrus). Predominantly right hemispheric activations were found in the fusiform gyrus, the right dorsolateral prefrontal cortex (inferior and middle frontal gyrus) and the superior parietal gyrus. In the elderly subjects, the activated areas in the right fronto-lateral cortex increased. An additional activated area could be found in the medial frontal gyrus (right > left). In the location-matching task, young subjects presented increased bilateral (right > left) activation in the superior parietal lobe and precuneus compared with face matching. The activations in the occipito-temporal pathway, in the right fronto-lateral cortex and the fusiform gyrus were similar to the activations found in the face-matching task. In the elderly subjects, we detected similar activation patterns compared to the young subjects with additional activations in the medial frontal gyrus. Conclusion: Activation patterns for object-based and spatial visual processing were established in the young and elderly healthy subjects. Differences between the elderly and young subjects could be evaluated, especially by using a face-matching task. Copyright (c) 2007 S. Karger AG, Basel

Developmental improvement and age-related decline in unfamiliar face matching

Age-related changes have been documented widely in studies of face recognition and eyewitness identification. However, it is not clear whether these changes arise from general developmental differences in memory or occur specifically during the perceptual processing of faces. We report two experiments to track such perceptual changes using a 1-in-10 (Experiment 1) and 1-in-1 (Experiment 2) matching task for unfamiliar faces. Both experiments showed improvements in face matching during childhood and adult-like accuracy levels by adolescence. In addition, face-matching performance declined in adults of the age of 65. These findings indicate that developmental improvements and aging-related differences in face processing arise from changes in the perceptual encoding of faces. A clear face inversion effect was also present in all age groups. This indicates that those age-related changes in face matching reflect a quantitative effect, whereby typical face processes are engaged but do not operate at the best-possible level. These data suggest that part of the problem of eyewitness identification in children and elderly persons might reflect impairments in the perceptual processing of unfamiliar faces

Coupled Deep Learning for Heterogeneous Face Recognition

Heterogeneous face matching is a challenge issue in face recognition due to large domain difference as well as insufficient pairwise images in different modalities during training. This paper proposes a coupled deep learning (CDL) approach for the heterogeneous face matching. CDL seeks a shared feature space in which the heterogeneous face matching problem can be approximately treated as a homogeneous face matching problem. The objective function of CDL mainly includes two parts. The first part contains a trace norm and a block-diagonal prior as relevance constraints, which not only make unpaired images from multiple modalities be clustered and correlated, but also regularize the parameters to alleviate overfitting. An approximate variational formulation is introduced to deal with the difficulties of optimizing low-rank constraint directly. The second part contains a cross modal ranking among triplet domain specific images to maximize the margin for different identities and increase data for a small amount of training samples. Besides, an alternating minimization method is employed to iteratively update the parameters of CDL. Experimental results show that CDL achieves better performance on the challenging CASIA NIR-VIS 2.0 face recognition database, the IIIT-D Sketch database, the CUHK Face Sketch (CUFS), and the CUHK Face Sketch FERET (CUFSF), which significantly outperforms state-of-the-art heterogeneous face recognition methods.Comment: AAAI 201

Perceptual impairment in face identification with poor sleep

Previous studies have shown impaired memory for faces following restricted sleep. However, it is not known whether lack of sleep impairs performance on face identification tasks that do not rely on recognition memory, despite these tasks being more prevalent in security and forensic professions—for example, in photo-ID checks at national borders. Here we tested whether poor sleep affects accuracy on a standard test of face-matching ability that does not place demands on memory: the Glasgow Face-Matching Task (GFMT). In Experiment 1, participants who reported sleep disturbance consistent with insomnia disorder show impaired accuracy on the GFMT when compared with participants reporting normal sleep behaviour. In Experiment 2, we then used a sleep diary method to compare GFMT accuracy in a control group to participants reporting poor sleep on three consecutive nights—and again found lower accuracy scores in the short sleep group. In both experiments, reduced face-matching accuracy in those with poorer sleep was not associated with lower confidence in their decisions, carrying implications for occupational settings where identification errors made with high confidence can have serious outcomes. These results suggest that sleep-related impairments in face memory reflect difficulties in perceptual encoding of identity, and point towards metacognitive impairment in face matching following poor sleep