Intelligent Computer Graphics 2012

Flowering plants have an enormous variety of shapes both within and between individuals, providing a vast area of objectives which the image synthesis must challenge. The structure of a flower has such properties as self-similarity, symmetry, branching arrangement, which make a modeling process quite tedious. We propose to apply mathematical methods to determine botanical natural laws, using 3Gmap L-systems. Describing the structure of a flowering plant with a grammar we are able to obtain an unlimited number of its geometrical interpretations. Our approach combines L-systems grammar writing with interactive control of parameter settings. The L-systems grammars are used for describing the entire model, with stems,stamens, petals, leaves, etc., by simply operating with 3Gmap volumes. The presented contributions will make the task of a user more obvious and intuitive enabling her/him to create more accurate models. 3Gmap L-systems grammars have a nested structure, enabling to use a huge amount of grammars in a more obvious way. Moreover the way the model is built allows us to take into account its internal structure. As the flower tissue is non-homogeneous, the possibility of obtaining its internal composition could be quite useful for rendering, allowing for instance to render more accurate subsurface scattering.

Generation and visualization systems based on the principle of text-to-scene are powerful systems but they are not dedicated to the particular domain of theatre. Text-to-scene systems provide an intuitive way to easily create 3D environments for non-expert users. In this paper we propose a text-to-scene system dedicated to the theatre, which generates a 3D view based on the descriptive elements extracted from the theatrical text. Such a tool is designed to encourage the emergence of new methods in staging, research and teaching in the domain of the theatre. The works presented in this paper enable the elements of a theatrical production to be manipulated, with both a textual view and a 3D view. The 3D view is obtained from an automatic generation of a 3D environment, based on elements of scenography identified into the text by the user. Semantic annotations are added into the theatrical text to automatically obtain a visualization of a 3D virtual scenography. To encode the descriptive properties, the user adds tags, which identify semantic and descriptive information into the theatrical text. The tags are then used to calculate the location and the orientation of characters and objects in the resulting virtual scenography. The tags are also used to identify the emotional states, the postures of the characters, as well as the duration of each state in order to generate views of the scene.

Higher Education Institutes worldwide are facing an increased demand to strengthen their capacities for research and innovation. This study introduces an ontology-based software system architecture that supports research policy evaluation processes and decision-making strategies, using visual analytics. A knowledge modeling technique drawing on multi criteria analysis and data visualisation is proposed. In addition, the paper presents a prototype built on Protegé, Pellet reasoner and Java Technologies, which is friendly to the user and capable of interactive synthesis of institutional decision support criteria. In this work we make a transition from knowledge to visual web-based decision support systems with different kinds of visualisations. The developed system enables research managers to evaluate key aspects of academic research activity in the context of specific policies and criteria, correlate strategic goals with research performance and make informed decisions on the establishment of research strategies.

This chapter deals with the problem of fitting curves to data points, a classical optimization problem in Computer-Aided Geometric Design (CAGD). This issue plays an important role in real problems such as construction of car bodies, ship hulls, airplane fuselage, and other free-form objects. A typical example comes from reverse engineering where free-form shapes are extracted from clouds of scanned data points. In this chapter we address this issue by applying a powerful bio-inspired method called Artificial Immune Systems (AIS). The AIS can be understood as a computational methodology based upon metaphors of the biological immune system. As such, there is not one but several AIS algorithms. In this chapter we focus on the clonal selection algorithm (CSA), which explicitly takes into account the affinity maturation of the immune response. This algorithm is applied to fit Bézier curves to given sets of data points. Some illustrative examples show the good performance of our approach.

We investigate the problem of determining design intent from engineering sketches: what did the designer have in mind when sketching a component? Specifically, we consider the unidirectional reverse mapping from form features, as determined from an input sketch, to design features, representing the design intent present in the designer’s mind. We introduce a list of common engineering form features. For each, we list which geometrical cues may be helpful in identifying these features in design sketches, and we list the design features which such form features commonly imply. We show that a reductionist approach which decomposes a diagram into form features can be used to deduce the design intent of the object portrayed in a drawing. We supply experimental results in support of this idea.

This chapter presents a current effort to model agent-personality using personality profile data extracted from individuals in the population. The obtained profiles are then used in a personality-driven behaviour engine to create realistic scenarios where massive evacuations can be simulated to promote awareness of the risks and emergency procedures in said scenarios.

Interactive drama and storytelling applications have become major issues in video games development. Prior research in interactive storytelling identified that adding narrative in computer games is a challenging task because: (i) it may restrict player interactivity, (ii) narrative causality/control, (iii) the duality between characters and plot, and (iv) the trade-off between narrative progression and user interaction. This chapter attempts to solve these problems by proposing an integrated framework for deeply combining interactivity and narrative in computer games workflow. It presents state-of-the-art results with respect to interactive drama and Petri nets (PN), and highlights some petri-net-based workflow tools for game design and game rules principles. The idea is to compose the game rules in the game’s workflow environment by different triggers and effects; and separates the rules of the game environment into two parts: controllable and noncontrollable rules. The main contribution of this chapter is to show how workflow management concepts can be jointly utilized with Petri nets (PN) for modeling game systems and game workflow control. Evaluation and performance results supported by some case study called “crazy ball 2” are also demonstrated. “Crazy ball 2” is a platform-type genre, much like the worldwide-known game Mario and the Konami’s Castlevania series.

More and more applications are relying on simulated crowds to populate films, games, and architecture. Decades of work in this area have produced agents that deftly avoid collisions, but the crowds still look stiff and false because agents do not socialize naturally with each other. On the other hand, ours is a new, expressive algorithm for adding social dynamics to crowds that breathes a new dimension of realism into simulations. Unlike previous approaches, our work allows agents to have multiple social encounters with other agents. We correctly allow interactions to evolve as time passes using the psychological area of transactional analysis. Additionally, we break from previous paradigms since we do not tie our approach to a specific obstacle avoidance algorithm. Instead our algorithm has a flexible architecture that will run with almost any obstacle avoidance algorithm. Finally, we allow for artist direction in our simulations, including bi-modal crowds and social environments that can be changed in real-time. Our results show that our social crowd algorithm runs in real-time with up to 4,000 agents with far more realistic behaviors than previously simulated.

In this paper, Whitted-style ray tracing is considered. Its particular features are: only point or directional light sources and only sharp shadows. Nevertheless, it is the most popular algorithm of photorealistic rendering. One of its basic operation is a determination of visibility between two scene positions, especially between the light position and an object point: the so-called shadow ray. To speed up this, the following techniques were developed: direct calculation (shadow rays), the shadow map algorithm, the shadow volume algorithm, and the light meshes method. In order to enhance the realism of calculated images, a lot of developments were performed to modify the algorithm so that it could generate (or more exactly simulate) soft shadows instead of theoretical sharp ones. Each of techniques mentioned above was modified to produce soft shadows. Only a very slow approach based on the direct calculation of shadow rays (often called “area shadows”) works without drawbacks. The shadow map and volume techniques are very sensitive to the relative positions of light sources and objects in the scene. In this paper, we describe an original lights visibility grid algorithm which is also a modification of the classical Whitted algorithm. Note that our algorithm generates images with blurred sharp shadows, i.e., it generates soft shadows. It does not depend on relative positions of light sources and object points. It was shown both theoretically and by numerical experiments that if the rendering complexity (the number of objects, the number of lights, the image resolution) increases the computation time of our algorithm becomes even less than that of the Whitted algorithm.

Procedural modeling of fire has been very practical and popular, but most of them are based on random parameters for the purpose of creating realistic looking flames, while physical based modeling is closer to the realism, but suffered by complicated algorithms and heavy computational requirement. Our new approach on fire does not use any physical parameters, but uses real-life fire images and applies image-based methods and statistical analysis. We visualize the shape and motion of fire to analyze them, which can be used a simple and realistic fire modeling. We employ principal component analysis (PCA) and take it to a new level by introducing “eigenfires”, which are eigenvectors of the covariance matrix of fire videos, from variety of high-definition videos of real fire to visualize and understand the track of fire movement and how different flames are located in various locations. Our system provides flexibility for the artists to manipulate the ordinary style of a flame and change it to another distinct shape using a series of weights that are assigned to each eigenfire. Our method is also efficient in terms of compact representation of fire motion as PCA allows compression by cutting high dimension data for almost the same quality of the video.

Creation of 3D content in networked environments is a growing field of research, and its application will be key in many sectors such as medicine, simulation and cultural heritage. However, not many solutions exist that are able to use and manage 3D objects in such environments. In this paper, we present an architecture for the intelligent creation of imaginary worlds for running in a networked environment using technologies from disparate fields. This intelligent creation of an imaginary world enables end users to interactively run or walk within a 3D world. In order to improve the immersion experience we propose the use of external devices such as a treadmill and headphones with microphone. In this manner, users will interact with the system and with other users. The key components in the proposed architecture are a multiuser server, which will enable interaction among users, and a content server, which will piece together geospatial data and 3D media objects to automatically build the imaginary world and augment it with real data.

We present a novel pipeline for the construction of biomechanical simulations by combining generic anatomical knowledge with specific data. Based on functional descriptors supplied by the user, the list of the involved anatomical entities (currently bones and muscles) is generated using formal knowledge stored in ontologies, as well as a physical model based on reference geometry and mechanical parameters. This simulation-ready model can then be registered to subject-specific geometry to perform customized simulations.

The user can provide additional specific geometry, such as a simulation mesh, to assemble with the reference geometry. Subject-specific information can also be used to individualize each functional model. The model can then be visualized and animated.

This pipeline dramatically eases the creation of biomechanical models. We detail an example of a musculoskeletal simulation of knee flexion and hip flexion and abduction, based on rigid bones and the Hill muscle model, with subject-specific 3D meshes non-rigidly attached to the simulated bones.

Recent years have seen an exponential increase in the use of mobile devices. Since many of the mobile devices are equipped with a camera and are connected to the internet, localization in an urban environment using landmark images is gaining popularity. The idea is simple. A tourist takes images of a landmark where he or she is standing with a mobile camera which are then transmitted to a server where the image(s) are matched against a database of landmark images for that locality. If a match is found, relevant information such as background information on the landmark, nearby transit facilities or information on other important landmarks nearby is sent back. This type of application has tremendous potential as a mobile city guide or navigation aid. In this paper, we investigate the use of local invariant shape features and global features such as colour and texture for the recognition task as evident from literature and present various retrieval techniques. A variety of descriptors for landmark recognition and scene classification are discussed. Insights into vocabulary building and weighting schemes for representing landmark images are provided that can help in boosting recognition rates.

The main emphasis of this article lies in introducing the conception for the commercial implementation of a knowledge base for models of campus infrastructure, which satisfies real practical requirements. The focus is not merely on theoretically elaborated data and knowledge models, but on real comprehensive data and knowledge assets. The conception synthesizes an entire existing infrastructure database and exemplary implantations of separate knowledge-based systems. The aim is to develop a prototype of a commercially useable system with an industrial emphasis by combining knowledge-based systems with related powerful software tools. The focus of constructional engineering aspects lies in using the standardized data formats, field-specific norms as well as standards and selected applications of the campus domain. From the perspective of informatics it aims to develop an expert system for processing knowledge on the basis of using “CWSM GmbH Software Solutions Dresden” existing systematic data model and already developed powerful software tools. Thereby, HTW Dresden university campus serves as a real case of application.