Études psychophysiques sur la perception visuelle du bruit de rendu de Monte Carlo

Les images photoréalistes générées par des algorithmes de rendu physique utilisant la méthode de Monte Carlo induisent la présence de bruit visuel qui diminue lorsque le temps de calcul augmente. Nos travaux ont pour but de mieux comprendre la perception humaine de ce bruit afin d’optimiser le temps de calcul sans perte détectable de qualité des images. Le concept de bruit dans des images est une notion mal connue des participants naïfs. Cela pose certains défis méthodologiques car il nous a fallu adapter les paradigmes conventionnellement utilisées dans les tâches de recherche visuelle. Au cours de notre première étude, nous avons fait varier le niveau de bruit d’une partie de la scène en utilisant la méthode adaptative Quest+. Le seuil perceptif à 50% a été obtenu à partir de l’estimation de la fonction psychométrique. Dans une seconde tâche, les observateurs devaient détecter une différence de qualité en utilisant uniquement leur vision périphérique. Les résultats de cette étude ont révélé que les participants utilisent principalement leur vision centrale pour détecter une dégradation de la qualité de l'image. Les études écologiques dans la recherche de la qualité de l'image sont nécessaires pour permettre de comprendre la perception dans des conditions réelles. Nous avons mis en place une étude en ligne et nous avons collecté des données dans les deux conditions (laboratoire, en ligne). La comparaison des résultats a montré qu'il n'y a pas de différence significative entre les seuils mesurés dans ces différentes conditions. Enfin, nous nous sommes intéressé aux effets des scènes et des textures sur le seuil perceptif et les fixations. Ces analyses nous ont permis de remarquer que les zones non texturées et les plus claires sont les plus fixées et les plus utilisées pour déterminer la présence de bruit. Afin de prédire les fixations humaines nous avons proposé une nouvelle approche en calculant une carte de saillance sur la différenc e de deux images ayant des niveaux de bruit différents. Cette carte est une meilleure prédiction que la carte de saillance calculée sur une seule image pour la tache de détection du bruit. L’ensemble de nos résultats, s’appuyant sur la perception visuelle humaine, peuvent contribuer à améliorer les méthodes de rendu physique réalistes.Computer-generated images are now commonly used in printed or electronic media. The physically-based rendering using the Monte Carlo method to produce these images induces the presence of visual noise which decreases when the computation time increases. Our research aims at better understanding the human perception of this noise to optimize the computation time without detectable loss of image quality. However, investigating noise perception creates some methodological challenges. The conventional paradigms used in visual search and scene viewing tasks are not well suited to measure noise perception because the definition of noise is an unfamiliar concept to naive participants. In our first study, we varied the noise level of a part of the scene using the adaptive method Quest+. The perceptual threshold at 50% was obtained from the estimated psychometric function. In a second task, observers were asked to detect a quality difference using only their peripheral vision. Our results revealed that participants are using primarily their most central vision to detect a degradation in image quality. Ecological studies in image quality research are needed to understand noise perception under real-world conditions. We implemented an online study and collected data in both conditions (laboratory, online). The comparison of the results showed that there was no significant difference between the thresholds measured in the different conditions. Finally, we investigated the effects of scenes and textures on perceptual threshold and fixation paths. These findings revealed that the non-textured and brightest areas are the most fixated and the most used to detect the presence of noise. In order to predict human fixations we proposed a new approach by computing a saliency map of the difference of two images with different noise levels. This map is a better prediction than the saliency map calculated on a single image for the noise detection task. Overall , our results, grounded on human visual perception, may contribute to improving realistic physically-based rendering methods

Études psychophysiques sur la perception visuelle du bruit de rendu de Monte Carlo

Computer-generated images are now commonly used in printed or electronic media. The physically-based rendering using the Monte Carlo method to produce these images induces the presence of visual noise which decreases when the computation time increases. Our research aims at better understanding the human perception of this noise to optimize the computation time without detectable loss of image quality. However, investigating noise perception creates some methodological challenges. The conventional paradigms used in visual search and scene viewing tasks are not well suited to measure noise perception because the definition of noise is an unfamiliar concept to naive participants. In our first study, we varied the noise level of a part of the scene using the adaptive method Quest+. The perceptual threshold at 50% was obtained from the estimated psychometric function. In a second task, observers were asked to detect a quality difference using only their peripheral vision. Our results revealed that participants are using primarily their most central vision to detect a degradation in image quality. Ecological studies in image quality research are needed to understand noise perception under real-world conditions. We implemented an online study and collected data in both conditions (laboratory, online). The comparison of the results showed that there was no significant difference between the thresholds measured in the different conditions. Finally, we investigated the effects of scenes and textures on perceptual threshold and fixation paths. These findings revealed that the non-textured and brightest areas are the most fixated and the most used to detect the presence of noise. In order to predict human fixations we proposed a new approach by computing a saliency map of the difference of two images with different noise levels. This map is a better prediction than the saliency map calculated on a single image for the noise detection task. Overall , our results, grounded on human visual perception, may contribute to improving realistic physically-based rendering methods.Les images photoréalistes générées par des algorithmes de rendu physique utilisant la méthode de Monte Carlo induisent la présence de bruit visuel qui diminue lorsque le temps de calcul augmente. Nos travaux ont pour but de mieux comprendre la perception humaine de ce bruit afin d’optimiser le temps de calcul sans perte détectable de qualité des images. Le concept de bruit dans des images est une notion mal connue des participants naïfs. Cela pose certains défis méthodologiques car il nous a fallu adapter les paradigmes conventionnellement utilisées dans les tâches de recherche visuelle. Au cours de notre première étude, nous avons fait varier le niveau de bruit d’une partie de la scène en utilisant la méthode adaptative Quest+. Le seuil perceptif à 50% a été obtenu à partir de l’estimation de la fonction psychométrique. Dans une seconde tâche, les observateurs devaient détecter une différence de qualité en utilisant uniquement leur vision périphérique. Les résultats de cette étude ont révélé que les participants utilisent principalement leur vision centrale pour détecter une dégradation de la qualité de l'image. Les études écologiques dans la recherche de la qualité de l'image sont nécessaires pour permettre de comprendre la perception dans des conditions réelles. Nous avons mis en place une étude en ligne et nous avons collecté des données dans les deux conditions (laboratoire, en ligne). La comparaison des résultats a montré qu'il n'y a pas de différence significative entre les seuils mesurés dans ces différentes conditions. Enfin, nous nous sommes intéressé aux effets des scènes et des textures sur le seuil perceptif et les fixations. Ces analyses nous ont permis de remarquer que les zones non texturées et les plus claires sont les plus fixées et les plus utilisées pour déterminer la présence de bruit. Afin de prédire les fixations humaines nous avons proposé une nouvelle approche en calculant une carte de saillance sur la différenc e de deux images ayant des niveaux de bruit différents. Cette carte est une meilleure prédiction que la carte de saillance calculée sur une seule image pour la tache de détection du bruit. L’ensemble de nos résultats, s’appuyant sur la perception visuelle humaine, peuvent contribuer à améliorer les méthodes de rendu physique réalistes

A mathematical programming model for MSW management: A study of Attica

175 σ.Η διαχείριση των Αστικών Στερεών Αποβλήτων (ΑΣΑ) αποτελεί ένα σύνθετο πρόβλημα της σύγχρονης εποχής με επιπτώσεις τόσο περιβαλλοντικές όσο και οικονομικές. Επομένως, καθίσταται πρωταρχική ανάγκη η ολοκληρωμένη σχεδίαση ενός συστήματος διαχείρισης ΑΣΑ σε περιφερειακό επίπεδο. Στην παρούσα εργασία αναπτύσσεται ένα τέτοιο σύστημα που καλύπτει ένα εικοσαετή ορίζοντα σε περιφερειακό επίπεδο με τη χρήση Μαθηματικού Προγραμματισμού (ΜΠ). Το μοντέλο του ΜΠ είναι πολυπεριοδικό και στοχεύει στη δομική, διαστασιολογική και λειτουργική βελτιστοποίηση. Περιγράφει την υπερδομή του συστήματος και μέσω της πολυκριτηριακής βελτιστοποίησης παρέχεται το σύνολο των κατά Pareto βέλτιστων λύσεων του συστήματος. Η πληροφορία αυτή είναι απαραίτητη για τη λήψη αποφάσεων καθώς καθορίζει τη δομή του συστήματος (διεργασίες), τον σχεδιασμό (χωρητικότητα των μονάδων) και τη λειτουργία (ετήσιες ροές). Με βάση τις μεταβλητές απόφασης που είναι συνεχείς και ακέραιες, το μοντέλο αυτό κατατάσσεται σε μοντέλο Μικτού Ακέραιου Γραμμικού Προγραμματισμού (ΜΑΓΠ) και το υπολογιστικό εργαλείο που χρησιμοποιήθηκε είναι η GAMS (General Algebraic Modeling System). Στο παρόν μοντέλο η βελτιστοποίηση γίνεται με βάση δύο αντικειμενικές συναρτήσεις (κριτήρια): την οικονομική που προσδιορίζει την ελαχιστοποίηση της Καθαρής Παρούσας Αξίας (ΚΠΑ) και την περιβαλλοντική που προσδιορίζει την ελαχιστοποίηση των σχετικών ισοδύναμων εκπομπών CO2. Η εφαρμογή του πραγματοποιήθηκε στην περιοχή της Αττικής, δηλαδή σε μία πόλη περίπου 5.000.000 κατοίκων με ελληνικά χαρακτηριστικά σε ότι αφορά στην ποσότητα και στη σύνθεση των απορριμμάτων. Οι τεχνολογίες που μελετήθηκαν είναι η υγειονομική ταφή (LDF), η θερμική επεξεργασία (WTE), η βιολογική –μηχανική επεξεργασία (MBT), η βιολογική ξήρανση (BD), η κομποστοποίηση (CMP), η αναερόβια χώνευση (AD) και η ανάκτηση υλικών (MRF). Τα διαφορετικά σενάρια που εξετάστηκαν στην παρούσα εργασία είναι παραλλαγές για τις τιμές των ανακυκλώσιμων, για τις ποσότητες των απορριμμάτων που αντιστοιχούν στην Αττική, για την τιμή και την ποσότητα του παραγόμενου καυσίμου. Τα συμπεράσματα τα οποία προέκυψαν κατά τη συσχέτιση των επιλογών από οικονομικής και περιβαλλοντικής σκοπιάς μαρτυρούν την πορεία της εν λόγω έρευνας και αποτελούν ερεθίσματα για περαιτέρω μελέτη.The Municipal Solid Waste (MSW) management is a complex problem of modern society with impact both economic and environmental. Therefore, the need of the design of an integrated solid waste management system at regional level becomes urgent. This paper describes such a system covering a twenty – year horizon at a regional level using Mathematical Programming (MP). The model of MP is multi periodic and aims at structural, design and operational optimization. It describes the superstructure of the system and through Multi – Objective optimization it provides the set of Pareto optimal solution of the system. This information is essential to the decision – maker as it determines the structure of the system (processes), the design (capacity of units) and the operation (annual flows). Due to the fact that the decision variables are continuous and integer, this model is classified into Mixed Integer Linear Programming (MILP), using the widely known modeling system GAMS (General Algebraic Modeling System). In this model, the optimization is carried out based on two objective functions: the economic objective function which indicates the minimization of the Net Present Value (NPV) and the environmental objective function which identifies the minimization of the associated CO2 – equivalent emissions. The implementation took place in Attica, a city of about 5.000.000 residents with Greek characteristics in terms of waste amounts and composition of garbage. The technologies which are studied are Landfill (LDF), Waste to Energy (WTE), Mechanical & Biological Treatment (MBT), Biodrying (BD), Composting (CMP), Anaerobic Digestion (AD) and Material Recycling Facilities (MRF). The different scenarios being considered in this paper are changes regarding the price of recyclables, the quantities of waste in Attica, the price and the quantity of derived fuel. The conclusions of this case-study, which were drawn through the correlation of choices in economic and environmental terms, indicate the course of this research and constitute a stepping stone for a further study.Βασιλική Γ. Μυρωδι

Pointing at static targets in a virtual reality environment: performance of visually impaired vs. normally-sighted persons

International audienc

Pointing at static targets in a virtual reality environment: performance of visually impaired vs. normally-sighted persons

International audienceVirtual reality (VR) offers innovative perspectives in the field of visual impairment. The general and exploratory goal of this study was to investigate how well the patients performed a pointing task compared to normally-sighted controls. We also assessed whether the characteristics of patients’ scotoma correlated with their performance in our pointing task. Normally-sighted and visually impaired subjects participated in a head contingent task developed with PTVR (https://ptvr.inria.fr/). Subjects had to move their head to point with a head-contingent reticle at a static target in the virtual environment. Pointing had to be maintained for 2 seconds to be validated (a timeout occurred after 30 sec without valid pointing). Reticle position in the headset’s viewport was either in the center (centered condition) or 10° from the center at one of the 8 possible half-meridians (eccentric condition). An additional perimetric exam was conducted for patients using a microperimeter (MP-3 Nidek Inc.), thus providing information about the position and shape of the scotoma. Our main dependent variable was the time needed to achieve valid pointing. We also estimated the accuracy of the subjects’ performance. Accuracy is the percentage of trials validated by the subject during the experiment. Linear mixed-effects models were used to analyze the reaction times of all subjects. Our preliminary data (N=8) show that visually impaired subjects are able to perform our head-contingent task. Although the reaction times were longer in the patients’ group (mean, 12.4 sec) than in the control group (mean, 4.6 sec). Patients had lower accuracy (87%) than normally-sighted subjects (100%). For the patients’ group, the results indicate an anisotropy of pointing performance across the reticle’s positions. Microperimetry data will help to understand how this idiosyncratic anisotropy may be related to the characteristics of each subject's scotoma. These data will help us develop rehabilitation tools based on pointing tasks

PTVR - a visual perception software in Python to make virtual reality experiments easier to build and more reproducible

Researchers increasingly use Virtual Reality (VR) to perform behavioral experiments, especially in Vision Science. These experiments are usually programmed directly in so-called game engines that are extremely powerful. However, this process is tricky and time-consuming as it requires solid knowledge of game engines. Consequently, the anticipated prohibitive effort discourages many researchers who want to engage in VR. This paper introduces the Perception Toolbox for Virtual Reality (PTVR) library, allowing visual perception studies in VR to be created using high-level Python script programming. A crucial consequence of using a script is that an experiment can be described by a single, easy-to-read piece of code, thus improving VR studies' transparency, reproducibility, and reusability. We built our library upon a seminal open-source library released in 2018 that we have considerably developed since then. This paper aims to provide a comprehensive overview of the PTVR software for the first time. We introduce the main objects and features of PTVR and some general concepts related to the 3D world. This new library should dramatically reduce the difficulty of programming experiments in VR and elicit a whole new set of visual perception studies with high ecological validity

PTVR - a visual perception software in Python to make virtual reality experiments easier to build and more reproducible

Researchers increasingly use Virtual Reality (VR) to perform behavioral experiments, especially in Vision Science. These experiments are usually programmed directly in so-called game engines that are extremely powerful. However, this process is tricky and time-consuming as it requires solid knowledge of game engines. Consequently, the anticipated prohibitive effort discourages many researchers who want to engage in VR. This paper introduces the Perception Toolbox for Virtual Reality (PTVR) library, allowing visual perception studies in VR to be created using high-level Python script programming. A crucial consequence of using a script is that an experiment can be described by a single, easy-to-read piece of code, thus improving VR studies' transparency, reproducibility, and reusability. We built our library upon a seminal open-source library released in 2018 that we have considerably developed since then. This paper aims to provide a comprehensive overview of the PTVR software for the first time. We introduce the main objects and features of PTVR and some general concepts related to the 3D world. This new library should dramatically reduce the difficulty of programming experiments in VR and elicit a whole new set of visual perception studies with high ecological validity

Meet-U: Educating through research immersion.

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master's students in bioinformatics and modeling, with protein-protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org