49 research outputs found

    Synthesizing Human Motion From Intuitive Constraints

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    Many compelling applications would become feasible if novice users had the ability to synthesize high quality human motion based only on a simple sketch and a few easily specified constraints. Motion graphs and their variations have proven to be a powerful tool for synthesizing human motion when only a rough sketch is given. Motion graphs are simple to implement, and the synthesis can be fully automatic. When unrolled into the environment, motion graphs, however, grow drastically in size. The major challenge is then searching these large graphs for motions that satisfy user constraints. A number of sub-optimal algorithms that do not provide guarantees on the optimality of the solution have been proposed. In this paper, we argue that in many situations to get natural results an optimal or nearly-optimal search is required. We show how to use the well-known A* search to find solutions that are optimal or of bounded sub-optimality. We achieve this goal for large motion graphs by performing a lossless compression of the motion graph and implementing a heuristic function that significantly accelerates the search for the domain of human motion. We demonstrate the power of this approach by synthesizing optimal or near optimal motions that include a variety of behaviors in a single motion. These experiments show that motions become more natural as the optimality improves

    Egress Online: Towards Leveraging Massively, Multiplayer Environments for Evacuation Studies

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    Large datasets of real human behaviors are of huge benefit across numerous domains, including evacuation safety, urban planning, marketing, and ergonomics. However, because large-scale experiments involving real human subjects are expensive and prohibitively difficult to organize, such datasets are scarce. Thus in this paper, we propose the use of massively multiplayer online (MMO) communities as an inexpensive and innovative way to capture datasets of large numbers of people under different conditions. We describe our implementation of an online data collection system, based on games, inside the popular massively multiplayer, online environment of Second Life. We evaluate the use of this system for performing evacuation experiments using a mix of Second Life residents and players recruited on campus. Our system was able to draw online participants, support data collection needs, and provide potential insights into high-level evacuation behaviors such as the choices of exit, effects of building debris, and the use-patterns of a building. Through experiments performed using our system, we found that Second Life residents found the game controls and environment to be significantly more compelling than lab participants; that players unfamiliar with our office building tended to evacuate primarily via the front entrance; and that in-game debris significantly increased the numbers of participants who failed to exit a building safely

    Stochastic Activity Authoring With Direct User Control

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    Crowd activities are often randomized to create the appearance of heterogeneity. However, the parameters that control randomization are frequently hard to tune because it is unclear how changes at the character level affect the high-level appearance of the crowd. We propose a method for computing randomization parameters that supports direct animator control. Given details about the environment, available activities, timing information and the desired highlevel appearance of the crowd, we model the problem as a graph, formulate a convex optimization problem, and solve for a set of stochastic transition rates which satisfy the constraints. Unlike the use of heuristics for adding randomness to crowd activities, our approach provides guarantees on convergence to the desired result, allows for decentralized simulation, and supports a variety of constraints. In addition, because the rates can be pre-computed, no additional runtime processing is needed during simulation

    How Responsiveness Affects Players\u27 Perception in Digital Games

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    Digital games with realistic virtual characters have become very popular. The ability for players to promptly control their character is a crucial feature of these types of games, be it platform games, first-person shooters, or role-playing games. Controller latencies, meaning delays in the responsiveness of a player’s character, for example due to extensive computations or to network latencies, can considerably reduce the player’s enjoyment of a game. In this paper, we present a thorough analysis of the consequences of such delays on the player’s experience across three parts of a game with different levels of difficulty. We investigate the effects of responsiveness on the player’s enjoyment, performance, and perception of the game, as well as the player’s adaptability to delays. We find that responsiveness is very important for the player as delays affect the player’s enjoyment of the game as well as the player’s performance. A quick responsiveness becomes essential for more challenging tasks

    ONLINE FORUMS: COMMUNICATION MODEL, CATEGORIES OF ONLINE COMMUNICATION REGULATION AND NORMS OF BEHAVIOR

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    Purpose of the study: The paper addresses the issue of regulating Internet communication activities in the context of online forums. The study aims to create a forum communication model identifying the areas subject to social regulation and defining the most common types of norms Methodology: The study draws upon the semiotic method to develop a new communication model based on classical theories. Quantitative empirical studies are also used. The rules and guidelines of 1,205 online forums were analyzed to identify the most common norms. Main Findings: Communicators and moderators access the forum communication space via user accounts and create a sign system. Some categories, such as a ban on deceptive or offensive content, are similar to those used in offline life. Other regulations are Internet-specific in that they are determined by inherent challenges of online communication (for example, account cloning) or by the way a forum is structured. Applications of this study: The findings related to the forum rules are presented in a summarized manner, although the rules vary slightly in reality, depending on the forum topic. The prevalence of deviant behaviors on online forums was also beyond the scope of this study. The study was based on the rules of Russian- and English-speaking forums, and it should be noted that language differences could influence the results. Social Implications: The evolving social interactions on the Web require regulations, which can differ significantly from those used offline. The study of social norms on the Internet allows us to trace what types of online behavior are now considered deviant and examine the current potential of Internet self-regulation. Novelty/Originality of this study: The study developed a new communication model for categorizing online communication norms. Major categories of online communication behavior regulation were identified and the most popular types of social norms were determined

    Real-Time Graphic and Haptic Simulation of Deformable Tissue Puncture

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    A myriad of surgical tasks rely on puncturing tissue membranes (Fig. 1) and cutting through tissue mass. Properly training a practitioner for such tasks requires a simulator that can display both the graphical changes and the haptic forces of these deformations, punctures, and cutting actions. This paper documents our work to create a simulator that can model these effects in real time. Generating graphic and haptic output necessitates the use of a predictive model to track the tissue’s physical state. Many finite element methods (FEM) exist for computing tissue deformation ([1],[4]). These methods often obtain accurate results, but they can be computationally intensive for complex models. Real-time tasks using this approach are often limited in their complexity and workspace domain due to the large computational overhead of FEM. The computer graphics community has developed a large range of methods for modeling deformable media [5], often trading complete physical accuracy for computational speedup. Casson and Laugier [3] outline a mass-spring mesh model based on these principles, but they do not explore its usage with haptic interaction. Gerovich et al. [2] detail a set of haptic interaction rules (Fig. 2) for one dimensional simulation of multi-layer deformable tissue, but they do not provide strategies for integrating this model with realistic graphic feedback

    A Data-Driven Appearance Model for Human Fatigue

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    Humans become visibly tired during physical activity. After a set of squats, jumping jacks or walking up a flight of stairs, individuals start to pant, sweat, loose their balance, and flush. Simulating these physiological changes due to exertion and exhaustion on an animated character greatly enhances a motion’s realism. These fatigue factors depend on the mechanical, physical, and biochemical function states of the human body. The difficulty of simulating fatigue for character animation is due in part to the complex anatomy of the human body. We present a multi-modal capturing technique for acquiring synchronized biosignal data and motion capture data to enhance character animation. The fatigue model utilizes an anatomically derived model of the human body that includes a torso, organs, face, and rigged body. This model is then driven by biosignal output. Our animations show the wide range of exhaustion behaviors synthesized from real biological data output. We demonstrate the fatigue model by augmenting standard motion capture with exhaustion effects to produce more realistic appearance changes during three exercise examples. We compare the fatigue model with both simple procedural methods and a dense marker set data capture of exercise motions

    A GPU-Based Approach for Real-Time Haptic Rendering of 3D Fluids

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    Real-time haptic rendering of three-dimensional fluid flow will improve the interactivity and realism of video games and surgical simulators, but it remains a challenging undertaking due to its high computational cost. In this work we propose an innovative GPUbased approach that enables real-time haptic rendering of highresolution 3D Navier-Stokes fluids. We show that moving the vast majority of the computation to the GPU allows for the simulation of touchable fluids at resolutions and frame rates that are significantly higher than any other recent real-time methods without a need for pre-computations [Baxter and Lin 2004; Mora and Lee 2008; Dobashi et al. 2006]

    Corpus and Experimental Methods as the Components of the Cognitive Research of the Concept Language Policy

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    This article deals with the theoretical basis of cognitive research of the language policy concept. Corpus and experimental methods of the concept have been analyzed. The concept language policy is an object of different discourses, so as a language phenomenon it deals with the text taken into account the frequency of use, establishing a list of words related to this concept to establish the features of understanding the phenomenon of language policy by native speakers. The experimental techniques, namely, an associative experiment, the method of subjective definitions have been used. The corpus research methods have been applied to clarify the obtained results. Corpus-based and corpus-driven approaches to understand the concept have been analyzed. Some experimental methods have been used to study the content of the concept and its features. Such techniques allow obtaining information about the perception and interpretation of the concept under study by human consciousness. The study consists in the maximum coverage of the methods of analysis of the concept language policy. The theoretical component of the study of the concept language policy is analyzed. The aim of the article is to identify the necessity and possibility of combining several methods of studying the concept within the framework of linguocognitive analysis. To meet this aim, it is necessary to define the following objectives: 1) to describe the approaches to the corpus and experimental methods; 2) to point out the essence of corpus analyses; 3) to corpus analyses to identify the peculiarities of the concept`s content

    Path Planning With Adaptive Dimensionality

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    Path planning quickly becomes computationally hard as the dimensionality of the state-space increases. In this paper, we present a planning algorithm intended to speed up path planning for high-dimensional state-spaces such as robotic arms. The idea behind this work is that while planning in a highdimensional state-space is often necessary to ensure the feasibility of the resulting path, large portions of the path have a lower-dimensional structure. Based on this observation, our algorithm iteratively constructs a state-space of an adaptive dimensionality–a state-space that is high-dimensional only where the higher dimensionality is absolutely necessary for finding a feasible path. This often reduces drastically the size of the state-space, and as a result, the planning time and memory requirements. Analytically, we show that our method is complete and is guaranteed to find a solution if one exists, within a specified suboptimality bound. Experimentally, we apply the approach to 3D vehicle navigation (x, y, heading), and to a 7 DOF robotic arm on the Willow Garage’s PR2 robot. The results from our experiments suggest that our method can be substantially faster than some of the state-ofthe-art planning algorithms optimized for those tasks
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