This article introduces Film Editing Patterns (FEP) , a language to formalize film editing practices and stylistic choices found in movies. FEP constructs are constraints, expressed over one or more shots from a movie sequence, that characterize changes in cinematographic visual properties, such as shot sizes, camera angles, or layout of actors on the screen. We present the vocabulary of the FEP language, introduce its usage in analyzing styles from annotated film data, and describe how it can support users in the creative design of film sequences in 3D. More specifically, (i) we define the FEP language, (ii) we present an application to craft filmic sequences from 3D animated scenes that uses FEPs as a high level mean to select cameras and perform cuts between cameras that follow best practices in cinema, and (iii) we evaluate the benefits of FEPs by performing user experiments in which professional filmmakers and amateurs had to create cinematographic sequences. The evaluation suggests that users generally appreciate the idea of FEPs, and that it can effectively help novice and medium experienced users in crafting film sequences with little training.

In this paper, we concentrate on the problem of finding the viewpoint that best satisfies a set of visual composition properties, often referred to as Virtual Camera or Viewpoint Composition. Previous approaches in the literature, which are based on general optimization solvers, are limited in their practical applicability because of unsuitable computation times and limited experimental analysis. To bring performances much closer to the needs of interactive applications, we introduce novel ways to define visual properties, evaluate their satisfaction, and initialize the search for optimal viewpoints, and test them in several problems under various time budgets, quantifying also, for the first time in the domain, the importance of tuning the parameters that control the behavior of the solving process. While our solver, as others in the literature, is based on Particle Swarm Optimization, our contributions could be applied to any stochastic search process that solves through many viewpoint evaluations, such as the genetic algorithms employed by other papers in the literature. The complete source code of our approach, together with the scenes and problems we have employed, can be downloaded from https://bitbucket.org/rranon/smart-viewpoint-computation-lib.

We present the Director's Lens, an intelligent interactive assistant for crafting virtual cinematography using a motion-tracked hand-held device that can be aimed like a real camera. The system employs an intelligent cinematography engine that can compute, at the request of the filmmaker, a set of suitable camera placements for starting a shot. These suggestions represent semantically and cinematically distinct choices for visualizing the current narrative. In computing suggestions, the system considers established cinema conventions of continuity and composition along with the filmmaker's previous selected suggestions, and also his or her manually crafted camera compositions, by a machine learning component that adapts shot editing preferences from user-created camera edits. The result is a novel workflow based on interactive collaboration of human creativity with automated intelligence that enables efficient exploration of a wide range of cinematographic possibilities, and rapid production of computer-generated animated movies.

This demonstration shows how an automated assistant encoded with knowledge of cinematography practice can offer suggested viewpoints to a filmmaker operating a hand-held motion-tracked virtual camera device. Our system, called Director's Lens, uses an intelligent cinematography engine to compute, at the request of the filmmaker, a set of suitable camera placements for starting a shot that represent semantically and cinematically distinct choices for visualizing the current narrative. Editing decisions and hand-held camera compositions made by the user in turn influence the system's suggestions for subsequent shots. The result is a novel virtual cinematography workflow that enhances the filmmaker's creative potential by enabling efficient exploration of a wide range of computer-suggested cinematographic possibilities.

Arranging 3D objects in Virtual Environments can be a complex, error prone and time consuming task, especially for users who are not familiar with interfaces for 3D navigation and object manipulation. In this paper, we analyze and compare novice users' performance on 3D object arrangement tasks using three interfaces that differ in the views of the 3D environment they provide: the first one is based only on a first-person view; the second one combines the first-person view and a map view in which the zoom level is manually controlled by the user; the third one extends the second with automated assistance in controlling the map zoom level during object manipulation. Our study shows that users without prior experience in 3D object arrangement prefer and actually benefit from having a map view in addition to a first person view in object arrangement tasks.

This demo will illustrate the adaptive interface of an application (whose architecture and implementation have been presented in detail in [2]) for learning 3D Graphics programming (in the X3D ISO standard). The application situates users in a 3D Virtual Environment where they can learn by selecting and inspecting actual examples.

This paper reports our recent work within the EuroTeV project, aimed at designing a Multipurpose Virtual Laboratory (MVL) to support collaboration among several European institutes, working in the area of physics research. Specifically, we discuss the type of support MVL can provrde to knowledge creation and sharing within its community of users. We also highlight how the digital resources available in this environment might be reused by virtual communities of learners, thus helping to bridge the gap between the worlds of eScience work and education.

This paper presents a tool for the visual analysis of navigation patterns of moving entities, such as users, virtual characters, or vehicles in 3D Virtual Environments (VEs). The tool, called VU-Flow, provides a set of interactive visualizations that highlight interesting navigation behaviors of single or groups of moving entities that were the VE together or separately. The visualizations help to improve the design of VEs and to study the navigation behavior of users, e.g., during controlled experiments. Besides VEs, the proposed techniques could also be applied to visualize real-world data recorded by positioning systems, allowing one to employ VU-Flow in domains such as urban planning, transportation, and emergency response.

Virtual Reality (VR) interfaces to e-commerce sites have recently begun to appear on the Internet, promising to make the e shopping experience more natural, attractive, and fun for customers. Unfortunately, switching to a desktop VR design for an e-commerce site is not trivial and does not guarantee at all that the interface will be effective. In this paper, we first briefly discuss the potential advantages of these interfaces, stressing the need for a better approach to their design. Then, we present the directions we are following to build more usable and effective VR stores, i.e.: (i) reformulating design guidelines from real-world stores in the VR context, (ii) exploiting VR to create user empowerments that meet both customer and merchant needs, and (iii) personalizing the VR store to better reflect customer's taste, preferences, and interests. For each of the three directions, we illustrate and discuss a detailed case study.