Olivier Penacchio

Visual discomfort and the spatial distribution of Fourier energy

Quite independently of what they represent, some images provoke discomfort, and even headaches and seizures in susceptible individuals. The visual system has adapted to efficiently process the images it typically experiences, and in nature these images are usually scale-invariant. In this work, we sought to characterize the images responsible for discomfort in terms of their adherence to low-level statistical properties typically seen in natural scenes. It has been conventional to measure scale invariance in terms of the one-dimensional Fourier amplitude spectrum, by averaging amplitude over orientations in the Fourier domain. However, this loses information on the evenness with which information at various orientations is represented. We therefore fitted a two-dimensional surface (regular circular cone 1/f in logarithmic coordinates) to the two-dimensional amplitude spectrum. The extent to which the cone fitted the spectrum explained an average of 18% of the variance in judgments of discomfort from images including rural and urban scenes, works of non-representational art, images of buildings and animals, and images generated from randomly disposed discs of varying contrast and size. Weighting the spectrum prior to fitting the surface to allow for the spatial frequency tuning of contrast sensitivity explained an average of 27% of the variance. Adjusting the shape of the cone to take account of the generally greater energy in horizontal and vertical orientations improved the fit, but only slightly. Taken together, our findings show that a simple measure based on first principles of efficient coding and human visual sensitivity explained more variance than previously published algorithms. The algorithm has a low computational cost and we show that it can identify the images involved in cases that have reached the media because of complaints. We offer the algorithm as a tool for designers rather than as a simulation of the biological processes involved.

Names and shades of color for intrinsic image estimation

In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance.

Orientation to the sun by animals and its interaction with crypsis

Summary Orientation with respect to the sun has been observed in a wide range of species and has generally been interpreted in terms of thermoregulation and/or ultraviolet (UV) protection. For countershaded animals, orientation with respect to the sun may also result from the pressure to exploit the gradient of coloration optimally to enhance crypsis. Here, we use computational modelling to predict the optimal countershading pattern for an oriented body. We assess how camouflage performance declines as orientation varies using a computational model that incorporates realistic lighting environments. Once an optimal countershading pattern for crypsis has been chosen, we determine separately how UV protection/irradiation and solar thermal inflow fluctuate with orientation. We show that body orientations that could optimally use countershading to enhance crypsis are very similar to those that allow optimal solar heat inflow and UV protection. Our findings suggest that crypsis has been overlooked as a selective pressure on orientation and that new experiments should be designed to tease apart the respective roles of these different selective pressures. We propose potential experiments that could achieve this.

Three-Dimensional Camouflage: Exploiting Photons to Conceal Form

Many animals have a gradation of body color, termed “countershading,” where the areas that are typically exposed to more light are darker. One hypothesis is that this patterning enhances visual camouflage by making the retinal image of the animal match that of the background, a fundamentally two-dimensional theory. More controversially, countershading may also obliterate cues to three-dimensional (3D) shape delivered by shading. Despite relying on distinct cognitive mechanisms, these two potential functions hitherto have been amalgamated in the literature. It has previously not been possible to validate either hypothesis empirically, because there has been no general theory of optimal countershading that allows quantitative predictions to be made about the many environmental parameters involved. Here we unpack the logical distinction between using countershading for background matching and using it to obliterate 3D shape. We use computational modeling to determine the optimal coloration for the camouflage of 3D shape. Our model of 3D concealment is derived from the physics of light and informed by perceptual psychology: we simulate a 3D world that incorporates naturalistic lighting environments. The model allows us to predict countershading coloration for terrestrial environments, for any body shape and a wide range of ecologically relevant parameters. The approach can be generalized to any light distribution, including those underwater.

3D camouflage : exploiting photons to conceal form

Many animals have a gradation of body color, termed “countershading,” where the areas that are typically exposed to more light are darker. One hypothesis is that this patterning enhances visual camouflage by making the retinal image of the animal match that of the background, a fundamentally two-dimensional theory. More controversially, countershading may also obliterate cues to three-dimensional (3D) shape delivered by shading. Despite relying on distinct cognitive mechanisms, these two potential functions hitherto have been amalgamated in the literature. It has previously not been possible to validate either hypothesis empirically, because there has been no general theory of optimal countershading that allows quantitative predictions to be made about the many environmental parameters involved. Here we unpack the logical distinction between using countershading for background matching and using it to obliterate 3D shape. We use computational modeling to determine the optimal coloration for the camouflage of 3D shape. Our model of 3D concealment is derived from the physics of light and informed by perceptual psychology: we simulate a 3D world that incorporates naturalistic lighting environments. The model allows us to predict countershading coloration for terrestrial environments, for any body shape and a wide range of ecologically relevant parameters. The approach can be generalized to any light distribution, including those underwater.

Optimizing countershading camouflage

Significance Because the sun and sky are above us, natural illumination is directional and the cues from shading reveal shape and depth. However, many animals are darker on their backs and, over 100 years ago, it was proposed that this phenomenon was camouflage: countering the cues to shape that directional illumination creates. However, does this camouflage work in practice? We predicted the optimal countershading for different lighting conditions and tested this possibility with correspondingly patterned model “caterpillars” predated by birds in the wild. Predation rates varied with coloration and lighting in exactly the manner predicted. Such subtlety in the effects of countershading vindicates conclusions from prior evidence demonstrating stronger countershading in animals in more brightly lit habitats. Countershading, the widespread tendency of animals to be darker on the side that receives strongest illumination, has classically been explained as an adaptation for camouflage: obliterating cues to 3D shape and enhancing background matching. However, there have only been two quantitative tests of whether the patterns observed in different species match the optimal shading to obliterate 3D cues, and no tests of whether optimal countershading actually improves concealment or survival. We use a mathematical model of the light field to predict the optimal countershading for concealment that is specific to the light environment and then test this prediction with correspondingly patterned model “caterpillars” exposed to avian predation in the field. We show that the optimal countershading is strongly illumination-dependent. A relatively sharp transition in surface patterning from dark to light is only optimal under direct solar illumination; if there is diffuse illumination from cloudy skies or shade, the pattern provides no advantage over homogeneous background-matching coloration. Conversely, a smoother gradation between dark and light is optimal under cloudy skies or shade. The demonstration of these illumination-dependent effects of different countershading patterns on predation risk strongly supports the comparative evidence showing that the type of countershading varies with light environment.

Intrinsic image evaluation on synthetic complex scenes

Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes.

A neurodynamical model of brightness induction in V1

Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway.

Coloresia: An Interactive Colour Perception Device for the Visually Impaired

A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves.

Establishing the behavioural limits for countershaded camouflage

Countershading is a ubiquitous patterning of animals whereby the side that typically faces the highest illumination is darker. When tuned to specific lighting conditions and body orientation with respect to the light field, countershading minimizes the gradient of light the body reflects by counterbalancing shadowing due to illumination, and has therefore classically been thought of as an adaptation for visual camouflage. However, whether and how crypsis degrades when body orientation with respect to the light field is non-optimal has never been studied. We tested the behavioural limits on body orientation for countershading to deliver effective visual camouflage. We asked human participants to detect a countershaded target in a simulated three-dimensional environment. The target was optimally coloured for crypsis in a reference orientation and was displayed at different orientations. Search performance dramatically improved for deviations beyond 15 degrees. Detection time was significantly shorter and accuracy significantly higher than when the target orientation matched the countershading pattern. This work demonstrates the importance of maintaining body orientation appropriate for the displayed camouflage pattern, suggesting a possible selective pressure for animals to orient themselves appropriately to enhance crypsis.