355,944 research outputs found

    The Role of Face Parts in Gender Recognition

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    This paper evaluates the discriminant capabilities of face parts in gender recognition. Given the image of a face, a number of subimages containing the eyes, nose, mouth, chin, right eye, internal face (eyes, nose, mouth, chin), external face (hair, ears, contour) and the full face are extracted and represented as appearance-based data vectors. A greater number of face parts from two databases of face images (instead of only one) were considered with respect to previous related works, along with several classification rules. Experiments proved that single face parts offer enough information to allow discrimination between genders with recognition rates that can reach 86%, while classifiers based on the joint contribution of internal parts can achieve rates above 90%. The best result using the full face was similar to those reported in general papers of gender recognition (>95%). A high degree of correlation was found among classifiers as regards their capacity to measure the relevance of face parts, but results were strongly dependent on the composition of the database. Finally, an evaluation of the complementarity between discriminant information from pairs of face parts reveals a high potential to define effective combinations of classifiers

    Learning Social Relation Traits from Face Images

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    Social relation defines the association, e.g, warm, friendliness, and dominance, between two or more people. Motivated by psychological studies, we investigate if such fine-grained and high-level relation traits can be characterised and quantified from face images in the wild. To address this challenging problem we propose a deep model that learns a rich face representation to capture gender, expression, head pose, and age-related attributes, and then performs pairwise-face reasoning for relation prediction. To learn from heterogeneous attribute sources, we formulate a new network architecture with a bridging layer to leverage the inherent correspondences among these datasets. It can also cope with missing target attribute labels. Extensive experiments show that our approach is effective for fine-grained social relation learning in images and videos.Comment: To appear in International Conference on Computer Vision (ICCV) 201

    Maori facial tattoo (Ta Moko): implications for face recognition processes.

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    Ta Moko is the art of the Maori tattoo. It was an integral aspect of Maori society and is currently seeing resurgence in popularity. In particular it is linked with ancestry and a sense of “Maori” pride. Ta Moko is traditionally worn by Maori males on the buttocks and on the face, while Maori women wear it on the chin and lips. With curvilinear lines and spiral patterns applied to the face with a dark pigment, the full facial Moko creates a striking appearance. Given our reliance on efficiently encoding faces this transformation could potentially interfere with how viewers normally process and recognise the human face (e.g. configural information). The pattern’s effects on recognising identity, expression, race, speech, and gender are considered, and implications are drawn, which could help wearers and viewers of Ta Moko understand why sustained attention (staring) is drawn to such especially unique faces

    Training methods for facial image comparison: a literature review

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    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, BĂŒlthoff & 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
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