Face recognition under varying pose: The role of texture and shape

Although remarkably robust, face recognition is not perfectly invariant to pose and viewpoint changes. It has been known since long, that the profile as well as the full-face view result in a recognition performance that is worse than a view from within that range. However, only few data exists that investigate this phenomenon in detail. This work intends to provide such data using a high angular resolution and a large range of poses. Since there are inconsistencies in the literature concerning these issues, we emphasize on the different role of the learning view and the testing view in the recognition experiment and on the role of information contained in the texture and in the shape of a face. Our stimuli were generated from laser-scanned head models and contained either the natural texture or only Lambertian shading and no texture. The results of our same/different face recognition experiments are: 1. Only the learning view but not the testing view effects the recognition performance. 2. For the textured faces the optimal learning view is closer to the full-face view than for the shaded faces. 3. For the shaded faces, we find a significantly better recognition performance for the symmetric view. The results can be interpreted in terms of different strategies to recover invariants from texture and from shading

Classifying faces by sex is more accurate with 3D shape information than with texture

Purpose: We compared quality of information available in 3D surface models versus texture maps for classifying human faces by sex. Methods: 3D surface models and texture maps from laser scans of 130 human heads (65 male, 65 female) were analyzed with separate principal components analyses (PCAs). Individual principal components (PCs) from the 3D head data characterized complex structural differences between male and female heads. Likewise, individual PCs in the texture analysis contrasted characteristically male vs. female texture patterns (e.g., presence/absence of facial hair shadowing). More formally, representing faces with only their projection coefficients onto the PCs, and varying the subspace from 1 to 50 dimensions, we trained a series of perceptrons to predict the sex of the faces using either the 3D or texture data. A "leave-one-out" technique was applied to measure the gen-eralizability of the perceptron's sex predictions. Results: While very good sex generalization performance was obtained for both representations, even with very low dimensional subspaces (e.g., 76.1 correct with only one 3D projection coefficient), the 3D data supported more accurate sex classification across nearly the entire range of subspaces tested. For texture, 93.8 correct sex generalization was achieved with a minimun subspace of 20 projection coefficients. For 3D data, 96.9 correct generalization was achieved with 17 projection coefficients. Conclusions: These data highlight the importance of considering the kinds of information available in different face representations with respect to the task demands

Panel: Bodily Expressed Emotion Understanding Research: A Multidisciplinary Perspective

Developing computational methods for bodily expressed emotion understanding can benefit from knowledge and approaches of multiple fields, including computer vision, robotics, psychology/psychiatry, graphics, data mining, machine learning, and movement analysis. The panel, consisting of active researchers in some closely-related fields, attempts to open a discussion on the future of this new and exciting research area. This paper documents the opinions expressed by the individual panelists

Amblyopic perception of biological motion

Although a number of low-level visual deficits in amblyopia have been identified, it is still unclear to what extent these deficits extend throughout the visual processing hierarchy. Biological motion perception can be a useful measure of local and global visual processing since the point-light stimuli that are often used to study this ability carry both local motion and global form information. To investigate the integrity of the biological motion processing system in amblyopia, we employed both detection and discrimination tasks with coherent or scrambled point-light walkers either alone or embedded in different types of point-light masks. These manipulations allowed for control over the amount of form and/or motion information available to the observers that could be used for task performance. We found that amblyopic eyes could process both the global form and local motion components of point-light walkers, indicating intact processing for these stimuli. However, amblyopic eyes did show an increased susceptibility to the addition of masking dots suggesting that segregation of signal from noise is deficient in amblyopia

Optimizing the colour and fabric of targets for the control of the tsetse fly Glossina fuscipes fuscipes

Background: Most cases of human African trypanosomiasis (HAT) start with a bite from one of the subspecies of Glossina fuscipes. Tsetse use a range of olfactory and visual stimuli to locate their hosts and this response can be exploited to lure tsetse to insecticide-treated targets thereby reducing transmission. To provide a rational basis for cost-effective designs of target, we undertook studies to identify the optimal target colour. Methodology/Principal Findings: On the Chamaunga islands of Lake Victoria , Kenya, studies were made of the numbers of G. fuscipes fuscipes attracted to targets consisting of a panel (25 cm square) of various coloured fabrics flanked by a panel (also 25 cm square) of fine black netting. Both panels were covered with an electrocuting grid to catch tsetse as they contacted the target. The reflectances of the 37 different-coloured cloth panels utilised in the study were measured spectrophotometrically. Catch was positively correlated with percentage reflectance at the blue (460 nm) wavelength and negatively correlated with reflectance at UV (360 nm) and green (520 nm) wavelengths. The best target was subjectively blue, with percentage reflectances of 3%, 29%, and 20% at 360 nm, 460 nm and 520 nm respectively. The worst target was also, subjectively, blue, but with high reflectances at UV (35% reflectance at 360 nm) wavelengths as well as blue (36% reflectance at 460 nm); the best low UV-reflecting blue caught 3× more tsetse than the high UV-reflecting blue. Conclusions/Significance: Insecticide-treated targets to control G. f. fuscipes should be blue with low reflectance in both the UV and green bands of the spectrum. Targets that are subjectively blue will perform poorly if they also reflect UV strongly. The selection of fabrics for targets should be guided by spectral analysis of the cloth across both the spectrum visible to humans and the UV region

Edge Detection in Landing Budgerigars (Melopsittacus undulatus)

Background: While considerable scientific effort has been devoted to studying how birds navigate over long distances, relatively little is known about how targets are detected, obstacles are avoided and smooth landings are orchestrated. Here we examine how visual features in the environment, such as contrasting edges, determine where a bird will land. Methodology/Principal Findings: Landing in budgerigars (Melopsittacus undulatus) was investigated by training them to fly from a perch to a feeder, and video-filming their landings. The feeder was placed on a grey disc that produced a contrasting edge against a uniformly blue background. We found that the birds tended to land primarily at the edge of the disc and walk to the feeder, even though the feeder was in the middle of the disc. This suggests that the birds were using the visual contrast at the boundary of the disc to target their landings. When the grey level of the disc was varied systematically, whilst keeping the blue background constant, there was one intermediate grey level at which the budgerigar's preference for the disc boundary disappeared. The budgerigars then landed randomly all over the test surface. Even though this disc is (for humans) clearly distinguishable from the blue background, it offers very little contrast against the background, in the red and green regions of the spectrum. Conclusions: We conclude that budgerigars use visual edges to target and guide landings. Calculations of photoreceptor excitation reveal that edge detection in landing budgerigars is performed by a color-blind luminance channel that sums the signals from the red and green photoreceptors, or, alternatively, receives input from the red double-cones. This finding has close parallels to vision in honeybees and primates, where edge detection and motion perception are also largely color-blind

Visual ecology of aphids – a critical review on the role of colours in host finding

We review the rich literature on behavioural responses of aphids (Hemiptera: Aphididae) to stimuli of different colours. Only in one species there are adequate physiological data on spectral sensitivity to explain behaviour crisply in mechanistic terms. Because of the great interest in aphid responses to coloured targets from an evolutionary, ecological and applied perspective, there is a substantial need to expand these studies to more species of aphids, and to quantify spectral properties of stimuli rigorously. We show that aphid responses to colours, at least for some species, are likely based on a specific colour opponency mechanism, with positive input from the green domain of the spectrum and negative input from the blue and/or UV region. We further demonstrate that the usual yellow preference of aphids encountered in field experiments is not a true colour preference but involves additional brightness effects. We discuss the implications for agriculture and sensory ecology, with special respect to the recent debate on autumn leaf colouration. We illustrate that recent evolutionary theories concerning aphid–tree interactions imply far-reaching assumptions on aphid responses to colours that are not likely to hold. Finally we also discuss the implications for developing and optimising strategies of aphid control and monitoring