Full-face Images Research Articles

Distinction between fear and surprise: an interpretation-independent test of the perceptual-attentional limitation hypothesis

ABSTRACTThe perceptual-attentional limitation hypothesis posits that the confusion between emotional facial expressions of fear and surprise may be due to their visual similarity, with shared muscle movements. In Experiment 1 full face images of fear and surprise varying as a function of distinctiveness (mouth index, brow index, or both indices) were displayed in a gender oddball task. Experiment 2, in a similar task, directed attention toward the eye or mouth region with a blurring technique. The current two studies used response time and event-related potentials (ERP) to test the perceptual-attentional limitation hypothesis. While ERP results for Experiment 1 suggested that individuals may not have perceived a difference between the emotional expressions in any of the conditions, response time results suggested that individuals processed a difference between fear and surprise when a distinctive cue was in the mouth. With directed attention in Experiment 2, ERP results indicated that individuals were capable of detecting a difference in all the conditions. In effect, the current two experiments suggest that participants display difficulty in distinguishing the prototypes of fear and surprise with the eye region, which may be due to a lack of attention to that region, providing support for the attentional limitation hypothesis.

An Efficient Method for Eye Detection in Color Images using Morphological Operations

This paper presents an efficient method for detecting human eye in a full frontal face color image. Eye regions are characterized by low illumination, high density edges and high contrast as compared to other parts in frontal face image. This method uses basic color image processing and morphological operation to detect eyes. Using color based training algorithm, this technique first extracts skin region of the input image. Then morphological operation is applied for detection of eye boundary and light source reflection of eye, also known as eye dot. It gives finite number of eye candidates from which noise is subsequently removed. For full frontal face images, this method is found highly efficient and accurate for eye detection.

Humans Process Dog and Human Facial Affect in Similar Ways

Humans share aspects of their facial affect with other species such as dogs. Here we asked whether untrained human observers with and without dog experience are sensitive to these aspects and recognize dog affect with better-than-chance accuracy. Additionally, we explored similarities in the way observers process dog and human expressions. The stimulus material comprised naturalistic facial expressions of pet dogs and human infants obtained through positive (i.e., play) and negative (i.e., social isolation) provocation. Affect recognition was assessed explicitly in a rating task using full face images and images cropped to reveal the eye region only. Additionally, affect recognition was assessed implicitly in a lexical decision task using full faces as primes and emotional words and pseudowords as targets. We found that untrained human observers rated full face dog expressions from the positive and negative condition more accurately than would be expected by chance. Although dog experience was unnecessary for this effect, it significantly facilitated performance. Additionally, we observed a range of similarities between human and dog face processing. First, the facial expressions of both species facilitated lexical decisions to affectively congruous target words suggesting that their processing was equally automatic. Second, both dog and human negative expressions were recognized from both full and cropped faces. Third, female observers were more sensitive to affective information than were male observers and this difference was comparable for dog and human expressions. Together, these results extend existing work on cross-species similarities in facial emotions and provide evidence that these similarities are naturally exploited when humans interact with dogs.

Automated Analysis of Binocular Alignment Using an Infrared Camera and Selective Wavelength Filter

We present a computerized method of measuring binocular alignment using a selective wavelength filter and an infrared camera, and validate the efficacy of automated image analysis compared to the gold standard prism and alternate cover test (PCT). A prospective observational pilot study was performed on 30 subjects with intermittent exotropia, 30 subjects with esotropia, and 30 orthotropic subjects who were able to cooperate with the PCT. Two independent ophthalmologists examined the angle of deviation using the PCT. Full-face images were obtained with an infrared camera while a selective wavelength filter was placed in front of either eye. Images were analyzed using the 3D Strabismus Photo Analyzer. Interobserver variability, test-retest reliability and correlation between the angles of deviation were determined for both methods. The 95% limit of agreement of interobserver variability was ± 4.8 prism diopters (PD) for the PCT and ± 4.3 PD for the selective wavelength filter analysis. The 95% limit of agreement of test-retest reliability between the PCT and selective wavelength filter analysis was ± 8.5 PD. Results of the PCT and selective wavelength filter analysis showed a strong positive correlation (R = 0.900, P < 0.001). Infrared images acquired with a selective wavelength filter can detect the latent components of strabismus, and automated image analysis showed excellent agreement with the standard PCT. This automated method is an accurate and reliable tool for measuring ocular deviation with minimal observer dependency.

Precedence of the Eye Region in Neural Processing of Faces

Functional magnetic resonance imaging (fMRI) has revealed multiple subregions in monkey inferior temporal cortex (IT) that are selective for images of faces over other objects. The earliest of these subregions, the posterior lateral face patch (PL), has not been studied previously at the neurophysiological level. Perhaps not surprisingly, we found that PL contains a high concentration of "face-selective" cells when tested with standard image sets comparable to those used previously to define the region at the level of fMRI. However, we here report that several different image sets and analytical approaches converge to show that nearly all face-selective PL cells are driven by the presence of a single eye in the context of a face outline. Most strikingly, images containing only an eye, even when incorrectly positioned in an outline, drove neurons nearly as well as full-face images, and face images lacking only this feature led to longer latency responses. Thus, bottom-up face processing is relatively local and linearly integrates features-consistent with parts-based models-grounding investigation of how the presence of a face is first inferred in the IT face processing hierarchy.

Remote identification of faces: Problems, prospects, and progress

Face recognition in unconstrained acquisition conditions is one of the most challenging problems that has been actively researched in recent years. It is well known that many state-of-the-art still face recognition algorithms perform well, when constrained (frontal, well illuminated, high-resolution, sharp, and full) face images are acquired. However, their performance degrades significantly when the test images contain variations that are not present in the training images. In this paper, we highlight some of the key issues in remote face recognition. We define the remote face recognition as one where faces are several tens of meters (10–250m) from the cameras. We then describe a remote face database which has been acquired in an unconstrained outdoor maritime environment. Recognition performance of a subset of existing still image-based face recognition algorithms is evaluated on the remote face data set. Further, we define the remote re-identification problem as matching a subject at one location with candidate sets acquired at a different location and over time in remote conditions. We provide preliminary experimental results on remote re-identification. It is demonstrated that in addition to applying a good classification algorithm, finding features that are robust to variations mentioned above and developing statistical models which can account for these variations are very important for remote face recognition.

Ultra-Rapid Categorization of Fourier-Spectrum Equalized Natural Images: Macaques and Humans Perform Similarly

BackgroundComparative studies of cognitive processes find similarities between humans and apes but also monkeys. Even high-level processes, like the ability to categorize classes of object from any natural scene under ultra-rapid time constraints, seem to be present in rhesus macaque monkeys (despite a smaller brain and the lack of language and a cultural background). An interesting and still open question concerns the degree to which the same images are treated with the same efficacy by humans and monkeys when a low level cue, the spatial frequency content, is controlled.Methodology/Principal FindingsWe used a set of natural images equalized in Fourier spectrum and asked whether it is still possible to categorize them as containing an animal and at what speed. One rhesus macaque monkey performed a forced-choice saccadic task with a good accuracy (67.5% and 76% for new and familiar images respectively) although performance was lower than with non-equalized images. Importantly, the minimum reaction time was still very fast (100 ms). We compared the performances of human subjects with the same setup and the same set of (new) images. Overall mean performance of humans was also lower than with original images (64% correct) but the minimum reaction time was still short (140 ms).ConclusionPerformances on individual images (% correct but not reaction times) for both humans and the monkey were significantly correlated suggesting that both species use similar features to perform the task. A similar advantage for full-face images was seen for both species. The results also suggest that local low spatial frequency information could be important, a finding that fits the theory that fast categorization relies on a rapid feedforward magnocellular signal.

A model of face space

Faces vary in their distinctiveness, and it has been suggested that—more distinctive faces are located further from the mean face in internal or perceptual face space (Valentine, 1991), than typical faces. This paper proposes a pixel-based computational model of face distinctiveness. I show that the notion of psychological distinctiveness is correlated with the metrical Euclidean distance, from the mean face. Distances are measured in pixel-based face space, which serves as the basis of the computational model. A prediction of the model is that pairwise perceptual distances between distinctive faces are, on average, greater than between typical faces. This is affirmed by psychophysical experiment. This finding confirms a key axiom of the norm-based coding model, which states that face space is centrally distributed with typical faces packed densely near the centre of the space and distinctive faces spread sparsely in the periphery. This assumption has previously been confirmed by Davidenko (2007) using face silhouettes, and here I show that this axiom also generalizes to full frontal face images.

Internal Facial Features are Signals of Personality and Health

We investigated forms of socially relevant information signalled from static images of the face. We created composite images from women scoring high and low values on personality and health dimensions and measured the accuracy of raters in discriminating high from low trait values. We also looked specifically at the information content within the internal facial features, by presenting the composite images with an occluding mask. Four of the Big Five traits were accurately discriminated on the basis of the internal facial features alone (conscientiousness was the exception), as was physical health. The addition of external features in the full-face images led to improved detection for extraversion and physical health and poorer performance on intellect/imagination (or openness). Visual appearance based on internal facial features alone can therefore accurately predict behavioural biases in the form of personality, as well as levels of physical health.

Computer assisted photo-anthropometric analyses of full-face and profile facial images

Expert witnesses using facial comparison techniques are regularly required to disambiguate cases of disputed identification in CCTV images and other photographic evidence in court. This paper describes a novel software-assisted photo-anthropometric facial landmark identification system, DigitalFace tested against a database of 70 full-face and profile images of young males meeting a similar description. The system produces 37 linear and 25 angular measurements across the two viewpoints. A series of 64 analyses were conducted to examine whether separate novel probe facial images of target individuals whose face dimensions were already stored within the database would be correctly identified as the same person. Identification verification was found to be unreliable unless multiple distance and angular measurements from both profile and full-face images were included in an analysis.

Computer-based evaluation of gender identification and morphologic classification of tooth face and arch forms

Statement of Problem. In prosthodontics, sex-related differences in tooth forms are assumed, and optimal esthetics is further assumed to be achieved only if the face, arch, and tooth forms are in harmony. However, there is no universally accepted rule or mathematical method to define these morphologic features. Purpose. The purpose of this study was to evaluate whether anterior tooth from reflected gender and to question the hypothesis that there was a correlation among face, arch, and tooth forms on the basis of dentists' perceptions. Material and Methods. Photographic records including full face, dental arch, and anterior tooth images of 60 dental students were made by use of digital photography. A database was arranged as a questionnaire for evaluation by prosthodontists who were asked to define the sex and morphologic features of the subjects by examining stored images of the subjects. Thirteen prosthodontists, all with at least 10 years of experience, served as experts and performed these evaluations twice at 2-week intervals. Kappa statistic was used to measure intraobserver and interobserver agreement. Results. The average correctly identified values in females and males were 53% and 58%, respectively. However, the proportions of females and males who were identified correctly and completely the same in both the first and second evaluations were 36% for females and 41% for males. According to the observations of the experts, face-to-arch form (54%) and face-to-tooth form (51%) correlations were higher than the tooth-to-arch form correlation. The overall correlation among face, arch, and tooth forms was 31%. The experts were in fair agreement in defining tooth forms. Conclusion. The results of gender identification of the subjects showed that the experts were unsuccessful in distinguishing the actual sex by the visual assessment of anterior tooth segment alone, with a fair agreement between 2 evaluation sessions. There were also significant interobserver and intraobserver differences in classifying face, arch, and especially tooth forms. Furthermore, the correlation among these forms was not highly defined. (J Prosthet Dent 2002;88:578-84.)