Guillaume Moreau

A new typology of augmented reality applications

In recent years Augmented Reality (AR) has become more and more popular, especially since the availability of mobile devices, such as smartphones or tablets, brought AR into our everyday life. Although the AR community has not yet agreed on a formal definition of AR, some work focused on proposing classifications of existing AR methods or applications. Such applications cover a wide variety of technologies, devices and goals, consequently existing taxonomies rely on multiple classification criteria that try to take into account AR applications diversity. In this paper we review existing taxonomies of augmented reality applications and we propose our own, which is based on (1) the number of degrees of freedom required by the tracking of the application, as well as on (2) the visualization mode used, (3) the temporal base of the displayed content and (4) the rendering modalities used in the application. Our taxonomy covers location-based services as well as more traditional vision-based AR applications. Although AR is mainly based on the visual sense, other rendering modalities are also covered by the same degree-of-freedom criterion in our classification.

Towards outdoor localization from GIS data and 3D content extracted from videos

We present an outdoor localization approach from videos and a 2D GIS (Geographic Information System). First, a 3D reconstruction as a cloud of points is done from the video with a Structure From Motion approach. Then a set of vertical planes is extracted from the cloud of points, using the presence of vanishing points in the video frames. This leads to a rough 3D model of the scene as a set of neighbor facades. That reconstruction will serve as an input data in a GIS localization query. Results of our reconstruction method are shown, based on a set of 27 videos of urban scenes.

Experiments on shape perception in stereoscopic displays

Stereoscopic displays are increasingly used for computer-aided design. The aim is to make virtual prototypes to avoid building real ones, so that time, money and raw materials are saved. But do we really know whether virtual displays render the objects in a realistic way to potential users? In this study, we have performed several experiments in which we compare two virtual shapes to their equivalent in the real world, each of these aiming at a specific issue by a comparison: First, we performed some perception tests to evaluate the importance of head tracking to evaluate if it is better to concentrate our efforts on stereoscopic vision; Second, we have studied the effects of interpupillary distance; Third, we studied the effects of the position of the main object in comparison with the screen. Two different tests are used, the first one using a well-known shape (a sphere) and the second one using an irregular shape but with almost the same colour and dimension. These two tests allow us to determine if symmetry is important in their perception. We show that head tracking has a more important effect on shape perception than stereoscopic vision, especially on depth perception because the subject is able to move around the scene. The study also shows that an object between the subject and the screen is perceived better than an object which is on the screen, even if the latter is better for the eye strain.

Transforming conceptual spatiotemporal model into object model with semantic keeping

Our work is developed in the context of spatiotemporal data modeling and more particularly of urban data modeling. Our goal is to propose a methodology describing the overall process of urban data modeling from the design phase to the implementation in an information system. For that, we propose, within a GIS, an approach based on a conceptual model specific to spatiotemporal data modeling MADS, and on an ODBMS for storing and manipulating data. MADS uses spatial and temporal types that are more precise than those of programming languages on which are based ODBMS. MADS is semantically richer than the object model, and the purpose of this paper is to present the transformation rules of this conceptual model into an object model that keeps (as close as possible) its semantics.

Implementing conceptual spatiotemporal model into object DBMS with semantic preserving

Our work is developed in the context of spatiotemporal data modeling and more particularly of urban data modeling. Our goal is to propose a methodology describing the overall process of urban data modeling beginning from the design phase until the implementation in an information system. For that, we propose, within a GIS, an approach based on a conceptual model specific to spatiotemporal data modeling MADS, and on an ODBMS for storing and manipulating data. MADS uses spatial, temporal and multi-representation types that are more precise than those of programming languages on which are based ODBMS models. Thus MADS is semantically richer than the object model, and the purpose of this paper is to present the transformation rules of this conceptual model into an object model that keeps (as close as possible) its semantics.

Pose computation based on Correspondence between 2D GIS and Street Images

This article presents a new approach to localization, especially relevant for use in dense urban environments. It is based on a correspondence between image data from pictures taken in the streets, and vector data from a GIS (Geographic Information System). First, a partial geometry of the outdoor scene is computed from the images, for instance angles and length ratios between visible facades. Secondly, this information is transformed into a GIS query, which results in a layer of the possible poses. Then, additional queries allow us to find only one pose, the true one. This can be considered as an alternative to GPS localization, since GPS may perform poorly in a dense urban environment. Moreover, it provides some information on the absolute orientation of the camera, which can be used for instance in Augmented Reality applications. This work is in fact one important step in the creation of a GIS‐connected Augmented Reality application, which will allow on site interaction with GIS data.

Influence of Being Embodied in an Obese Virtual Body on Shopping Behavior and Products Perception in VR

Research in Virtual Reality (VR) showed that embodiment can influence participants perceptions and behavior when embodied in a different yet plausible virtual body. In this paper, we study the changes an obese virtual body has on products perception (e.g., taste, etc.) and purchase behavior (e.g., number purchased) in an immersive virtual retail store. Participants (of a normal BMI on average) were embodied in a normal (N) or an obese (OB) virtual body and were asked to buy and evaluate food products in the immersive virtual store. Based on stereotypes that are classically associated with obese people, we expected that the group embodied in obese avatars would show a more unhealthy diet, (i.e., buy more food products and also buy more products with high energy intake, or saturated fat) and would rate unhealthy food as being tastier and healthier than participants embodied in “normal weight” avatars. Our participants also rated the perception of their virtual body: the OB group perceived their virtual body as significantly heavier and older. They also rated their sense of embodiment and presence within the immersive virtual store. These measures did not show any significant difference between groups. Finally, we asked them to rate different food products in terms of tastiness, healthiness, sustainability and price. The only difference we noticed is that participants embodied in an obese avatar (OB group) rated the coke as being significantly tastier and the apple as being significantly healthier. Nevertheless, while we hypothesized that participants embodied in a virtual body with obesity would show differences in their shopping patterns (e.g., more “unhealthy” products bought) there were no significant differences between the groups. Stereotype activation failed for our participants embodied in obese avatars, who did not exhibit a shopping behavior following the (negative) stereotypes related to obese people. conversely, while the opposite hypothesis (participants embodied in obese avatars would buy significantly more healthy products in order to “transform” their virtual bodies) could have been made, it was not the case either. We discuss these results and propose hypotheses as to why the behavior of the manipulated group differed from the one we expected. Indeed, unlike previous research, our participants were embodied in virtual avatars which differed greatly from their real bodies. Obese avatars should not only modify users visual characteristics such as hair or skin color, etc. We hypothesize that an obese virtual body may require some other non-visual stimulus, e.g., the sensation of the extra weight or the change in body size. This main difference could then explain why we did not notice any important modification on participants behavior and perceptions of food products. We also hypothesize that the absence of stereotype activation and thus of statistical difference between our N and OB groups might be due to higher-level cognitive processes involved while purchasing food products. Indeed our participants might have rejected their virtual bodies when performing the shopping task, while the embodiment and presence ratings did not show significant differences, and purchased products based on their real (non-obese) bodies. This could mean that stereotype activation is more complex that previously thought.

A study of virtual visual servoing sensitivity in the context of image/GIS registration for urban environments

This paper studies the sensitivity of pose estimation to the 2D measure noise when using virtual visual servoing. Attempting to apply virtual visual servoing to image/Geographic Information System (GIS) registration, the robustness to the noise in images is an important factor to the accuracy of estimation. To analyze the impact of different levels of noise, a series of image/GIS registration tests based on synthetic input image are studied. Also, RANSAC is introduced to improve the robustness of the method. We also compare some different strategies in choosing geometrical features and in the treatment of projection error vector in virtual visual servoing, providing a guide for parametrization.