Saliency maps of high dynamic range images

A number of computational models of visual attention have been proposed based on the concept of saliency map. Some of them have been validated as predictors of the visual scan-path of observers looking at images and videos, using oculometric data. They are widely used for Computer Graphics applications, mainly for image rendering, in order to avoid spending too much computing time on non salient areas, and in video coding, in order to keep a better image quality in salient areas. However, these algorithms were not used so far with High Dynamic Range (HDR) inputs. In this paper, we show that in the case of HDR images, the predictions using algorithms based on Itti et al. (1998) are less accurate than with 8-bit images. To improve the saliency computation for HDR inputs, we propose a new algorithm derived from Itti & Koch (2000). From an eye tracking experiment with a HDR scene, we show that this algorithm leads to good results for the saliency map computation, with a better fit between the saliency map and the ocular fixation map than Itti et al.'s algorithm. These results may impact image retargeting issues, for the display of HDR images on both LDR and HDR display devices

Alerting the drivers about road signs with poor visual saliency

This paper proposes an improvement of Advanced Driver Assistance System based on saliency estimation of road signs. After a road sign detection stage, its saliency is estimated using a SVM learning. A model of visual saliency linking the size of an object and a size-independent saliency is proposed. An eye tracking experiment in context close to driving proves that this computational evaluation of the saliency fits well with human perception, and demonstrates the applicability of the proposed estimator for improved ADAS

Filling the user skill gap using HCI techniques to implement experimental protocol on driving simulators

Abstract-Programming activities are performed not only by programmers but also by end-users in order to support their primary goals in different domains and applications. End-users do not have formal training in programming, so interaction environment and systems are needed, which could account for user skills. The objective of our work is to fill the gap between the user skills and the goals they want to achieve using driving simulators. This paper presents the results of a research in which, we have proposed a solution for the primary users of the driving simulator to design and implement experimental protocol. We have used user-centered design (UCD) technique, conducted a user survey, and proposed a solution, in which we have categorized the Interface of the driving simulator into three sub-interfaces based on the skills of the users. These interfaces are Experiment Builder (Nontechnical persons), Template builder (for technical persons) and Experiment Interface (for any user to execute experiment). A prototype based on this concept is developed and evaluated. Our results indicate that, users can implement an experimental protocol without having programming skills using our proposed design

La visibilité routière : une approche pluri-disciplinaire

-Nous nous inscrivons dans une approche pluri-disciplinaire en matière de recherche appliquée. Partant des besoins en matière de politique publique sur la perception visuelle dans les déplacements routiers et urbains, nous utilisons les connaissances issues de la recherche fondamentale en synthèse d'images et en sciences de la vision pour proposer des éléments de réponse. Nous associons ainsi des modèles théoriques en vision humaine (photométrie, psychophysique, neurosciences) et des problématiques liées à la visibilité routière (simulation de conduite, éclairage public, perception dans un trafic simulé). La démarche privilégiée consiste à utiliser des images de synthèse pour produire des connaissances sur la visibilité routière, notamment avec les méthodes de la psychologie expérimentale. D'autres approches sont également explorées (ergonomie cognitive, photométrie, intelligence artificielle). Les résultats académiques concernent des domaines variés : les calculs d'éclairage public pour la simulation de conduite, la visualisation des images de synthèse pour l'étude de la visibilité routière, la visibilité nocturne en conduite automobile, la saillance visuelle des objets routiers, ou la prise d'information visuelle pour la simulation de conduite et la simulation de trafic. Sur le plan des applications routières, nous avons contribué à la clarification du vocabulaire et des enjeux de la visibilité routière, ainsi qu'aux méthodes de diagnostic de la visibilité routière et de dimensionnement de l'éclairage public. Au cours des dernières années, nous avons également participé au développement de liens entre le LCPC et l'INRETS autour des problématiques de perception visuelle et de simulation de conduite. Nous avons notamment contribué en 2007 à la création d'un GIS sur la Simulation pour les Recherches sur la Sécurité Routière (SRSR), puis en 2009 à la création d'une unité mixte INRETS-LCPC, le Laboratoire Exploitation, Perception, Simulateurs et Simulations (LEPSiS). En conclusion, nous soutenons que notre travail contribue à faire émerger la visibilité routière comme une problématique scientifique légitime, que nous abordons à partir de la vision humaine et des images, à la fois images de synthèse et images issues de capteurs

Visual Performance Models in Road Lighting: A Historical Perspective

The use of visual performance models in road lighting is an old idea: it was first proposed in the 1930s by Waldram with the Revealing Power, and by Roper and Howard who used the notion of visibility distance. The Visibility Level (VL) concept was then proposed by Blackwell, and the Relative Visual Performance by Rea and Ouelette. At the turn of the 21th century, some standards have considered using the VL in order to rate lighting installations through the Small Target Visibility concept. However, the use of visual performance indexes in lighting standards was recently withdrawed, which raises a question: what happened

A Tone Mapping Operator for Road Visibility Experiments

One may wish to use computer graphic images to carry out road visibility studies. Unfortunatly, most display devices still have a limited luminance dynamic range, especially in driving simulators. In this paper, we propose a Tone Mapping Operator (TMO) to compress the luminance dynamic range while preserving the driver's performance for a visual task relevant for a driving situation. We address 3 display issues of some consequences for road image display: luminance dynamics, image quantization, and high minimum displayable luminance. Our TMO characterizes the effects of local adaptation with a bandpass decomposition of the image using a Laplacian pyramid, and processes the levels separately in order to mimic the Human Visual System. The contrast perception model uses the Visibility Level, a usual index in road visibility engineering applications. To assess our algorithm, a psychophysical experiment devoted to a target detection task was designed. Using a Landolt ring, the visual performances of 30 observers were measured: they stared first at a High Dynamic Range image, then at the same image processed by a TMO and displayed on a Low Dynamic Range monitor, for comparison. The evaluation was completed with a visual appearance evaluation. Our operator gives good performances for 3 typical road situations (one in daylight, two at night), after comparison with 4 standard TMOs from the literature. The psychovisual assessment of our TMO is limited to these driving situations

Case Studies in Learning Models and Testing Without Reset

International audienc

A High Dynamic Range Rendering Pipeline for Interactive Applications

High Dynamic Range (HDR) rendering has a growing success in video-games and virtual reality applications, as it improves the image quality and the player's immersion feeling. In this paper, we propose a new method, based on a physical lighting model, to compute in real time a HDR illumination in virtual environments. Our method allows to re-use existing virtual environments as input, and computes HDR images in photometric units. Then, from these HDR images, displayable 8-bit images are rendered with a tone mapping operator and displayed on a standard display device. The HDR computation and the tone mapping are implemented in OpenSceneGraph with pixel shaders. The lighting model, together with a perceptual tone mapping, improve the perceptual realism of the rendered images at low cost. The method is illustrated with a practical application where the dynamic range of the virtual environment is a key rendering issue : night-time driving simulation. This work will be published on the CGI 2010 conference

A High Dynamic Range Rendering Pipeline for Interactive Applications : in search for perceptual realism

Realistic images can be computed at interactive frame rates for Computer Graphics applications. Meanwhile, High Dynamic Range (HDR) rendering has a growing success in video games and virtual reality applications, as it improves the image quality and the player's immersion feeling. In this paper, we propose a new method, based on a physical lighting model, to compute in real time a HDR illumination in virtual environments. Our method allows to re-use existing virtual environments as input, and computes HDR images in photometric units. Then, from these HDR images, displayable 8-bit images are rendered with a tone mapping operator and displayed on a standard display device. The HDR computation and the tone mapping are implemented in OpenSceneGraph with pixel shaders. The lighting model, together with a perceptual tone mapping, improves the perceptual realism of the rendered images at low cost. The method is illustrated with a practical application where the dynamic range of the virtual environment is a key rendering issue: night-time driving simulation

Conception de l'éclairage routier : vers la prise en compte du contexte et de l'activité de conduite

La visibilité en conduite est primordiale, puisque c'est la détection des objets routiers qui permet au conducteur d'analyser et d'évaluer son environnement. La fonction principale de l'éclairage routier est d'améliorer la détection d'objets présents sur la chaussée la nuit, pour permettre leur évitement, et ce, grâce à l'anticipation rendue plus performante. L'effet de l'éclairage sur les performances visuelles est décrit au moyen de grandeurs photométriques, telles que l'éclairement, la luminance et le contraste. Le niveau de visibilité (VL) permet de quantifier la performance d'un observateur à partir du contraste de luminance. Le modèle classique proposé par Adrian (1989) permet le calcul du VL d'une petite cible sur un fond uniforme, et se fonde sur des données psycho-physiques de laboratoire (Blackwell, 1946). L'AFE le décrit comme suit : « le VL définit, pour un objet donné de luminance Lc, le rapport entre l'écart absolu de luminance objet/fond et l'écart absolu de luminance de l'objet/fond au seuil de visibilité, pour un état d'adaptation donné » (AFE, Recommandations relatives à l'éclairage des voies publiques, 2002, p.84). Dit autrement, VL=5 signifie que le contraste de luminance de la cible est 5 fois le contraste nécessaire pour détecter cette cible en situation de laboratoire. Le principal intérêt du VL pour décrire la visibilité est que, contrairement à d'autres indicateurs comme l'éclairement ou la luminance, il prend en compte la performance de détection d'une cible, qui est l'aspect de la conduite que l'éclairage routier vise à améliorer. En France, le VL est évoqué dans les Recommandations de l'AFE, mais aucun scénario de calcul et de mesure n'y est associé, ce qui rend cet indicateur peu opérationnel et contribue à sa faible utilisation par les praticiens. De plus, cet indicateur n'est pas mentionné dans la norme européenne EN 13201 (2005) traitant de l'éclairage public. Aux Etats-Unis, le VL sert de socle au modèle Small Target Visibility (STV), qui propose un scénario de mesure et utilise un « scénario de référence », centré sur la détection de cibles en situation de conduite (IESNA 2000)