Automatic view selection through depth-based view stability analysis

Although the real world is composed of three-dimensional objects, we communicate information using two-dimensional media. The initial 2D view we see of an object has great importance on how we perceive it. Deciding which of the all possible 2D representations of 3D objects communicates the maximum information to the user is still challenging, and it may be highly dependent on the addressed task. Psychophysical experiments have shown that three-quarter views (oblique views between frontal view and profile view) are often preferred as representative views for 3D objects; however, for most models, no knowledge of its proper orientation is provided. Our goal is the selection of informative views without any user intervention. In order to do so, we analyze some stability-based view descriptors and present a new one that computes view stability through the use of depth maps, without prior knowledge on the geometry or orientation of the object.We will show that it produces good views that, in most of the analyzed cases, are close to three-quarter views.Peer ReviewedPostprint (published version

Virtual camera selection using a semiring constraint satisfaction approach

Players and viewers of three-dimensional computer generated games and worlds view renderings from the viewpoint of a virtual camera. As such, determining a good view of the scene is important to present a good game or three-dimensional world. Previous research has developed technologies to nd good positions for the virtual camera, but little work has been done to automatically select between multiple virtual cameras, similar to a human director at a sporting event. This thesis describes a software tool to select among camera feeds from multiple virtual cameras in a virtual environment using semiring-based constraint satisfaction techniques (SCSP), a soft constraint approach. The system encodes a designer's preferences, and selects the best camera feed even in over-constrained or under-constrained environments. The system functions in real time for dynamic scenes using only current information (i.e. no prediction). To reduce the camera selection time the SCSP evaluation can be cached and converted to native code. This SCSP approach is implemented in two virtual environments: a virtual hockey game using a spectator viewpoint, and a virtual 3D maze game using a third person perspective. Comparisons against hard constraints are made using constraint satisfaction problems

Automatisation de la création de scénarios pour les scènes de la visualisation scientifique

RÉSUMÉ Bien que l’automatisation de la génération des chemins de caméra soit une pratique courante dans le cinéma et le jeu vidéo, elle fait preuve d’un retard important dans le milieu de la visualisation scientifique. La taille, la nature, la densité du maillage ainsi que l’absence de notions scénaristiques telles que les personnages et les actions font que l’opération d’import de règles de composition issues de domaines artistiques comme le cinéma ou la photographie ainsi que l’application des règles du montage deviennent plus complexe. Ce mémoire introduit une méthodologie qui propose une métamodélisation des attentes des scientifiques vis-à-vis de leurs données ainsi qu’une modélisation des comportements de données qui peuvent les intéresser. Ces modèles permettent de bâtir plus facilement des chemins de caméra pour des scènes numériques issues de simulations ou d’acquisitions. L’application des règles issues de la composition et du montage dans le but de produire des déplacements de caméra préservent l’intention du scientifique deviennent alors plus simple. La méthode a été expérimentée sur un ensemble de scènes issues de la mécanique des fluides et du génie biomédical; les résultats obtenus sur ces scènes nous ont permis de valider le fonctionnement de la méthodologie. Sont également proposés par la méthode un ensemble de paramètres de contrôle afin de modifier le processus de génération pour mieux l’adapter aux besoins précis que peut avoir un scientifique vis-à-vis d’une scène.----------ABSTRACT Automatic camera path generation is a common practice in film making and video games. However, it demonstrated a significant delay in scientific visualization due to the size, the nature, the mesh density and the lack of scriptwriting notions such as characters and actions. In this case, importing cinematography composition, photography composition and match cut rules becomes a more complex operation. This thesis presents a methodology that provides meta-models for the scientists' visualization expectations regarding their data and for the data behaviors that may interest them. These models make the camera paths generation process more intuitive. The application of composition and match cut rules, in order to produce camera moves that preserves the scientist's intention, becomes simpler. The method was tested on a set of scenes from fluid mechanics and biomedical engineering; the obtained results showed that our approach is a simple and efficient way for producing presentation videos. A set of control parameters are also provided by this method, in order to adapt the generation process to the specific needs that a scientist can have regarding his data

Information theory assisted data visualization and exploration

This thesis introduces techniques to utilize information theory, particularly entropy for enhancing data visualization and exploration. The ultimate goal with this work is to enable users to perceive as much as information available for recognizing objects, detecting regular or non-regular patterns and reducing user effort while executing the required tasks. We believe that the metrics to be set for enhancing computer generated visualizations should be quantifiable and that quantification should measure the information perception of the user. The proper way to solve this problem is utilizing information theory, particularly entropy. Entropy offers quantification of the information amount in a general communication system. In the communication model, information sender and information receiver are connected with a channel. We are inspired from this model and exploited it in a different way, namely we set the information sender as the data to be visualized, the information receiver as the viewer and the communication channel as the screen where the visualized image is displayed. In this thesis we explore the usage of entropy in three different visualization problems, -Enhancing the visualization of large scale social networks for better perception, -Finding the best representational images of a 3D object to visually inspect with minimal loss of information, -Automatic navigation over a 3D terrain with minimal loss of information. Visualization of large scale social networks is still a major challenge for information visualization researchers. When a thousand nodes are displayed on the screen with the lack of coloring, sizing and filtering mechanisms, the users generally do not perceive much on the first look. They usually use pointing devices or keyboard for zooming and panning to find the information that they are looking for. With this thesis we tried to present a visualization approach that uses coloring, sizing and filtering to help the users recognize the presented information. The second problem that we tried to tackle is finding the best representational images of 3D models. This problem is highly subjective in cognitive manner. The best or good definitions do not depend on any metric or any quantification, furthermore, when the same image is presented to two different users it can be identified differently. However in this thesis we tried to map some metrics to best or good definitions for representational images, such as showing the maximum faces, maximum saliency or combination of both in an image. The third problem that we tried to find a solution is automatic terrain navigation with minimal loss of information. The information to be quantified on this problem is taken as the surface visibility of a terrain. However the visibility problem is changed with the heuristic that users generally focus on city centers, buildings and interesting points during terrain exploration. In order to improve the information amount at the time of navigation, we should focus on those areas. Hence we employed the road network data, and set the heuristic that intersections of road network segments are the residential places. In this problem, region extraction using road network data, viewpoint entropy for camera positions, and automatic camera path generation methods are investigated

Automatic view selection through depth-based view stability analysis

Although the real world is composed of three-dimensional objects, we communicate information using two-dimensional media. The initial 2D view we see of an object has great importance on how we perceive it. Deciding which of the all possible 2D representations of 3D objects communicates the maximum information to the user is still challenging, and it may be highly dependent on the addressed task. Psychophysical experiments have shown that three-quarter views (oblique views between frontal view and profile view) are often preferred as representative views for 3D objects; however, for most models, no knowledge of its proper orientation is provided. Our goal is the selection of informative views without any user intervention. In order to do so, we analyze some stability-based view descriptors and present a new one that computes view stability through the use of depth maps, without prior knowledge on the geometry or orientation of the object.We will show that it produces good views that, in most of the analyzed cases, are close to three-quarter views.Peer Reviewe