1,403 research outputs found

    Feeling crowded yet?: Crowd simulations for VR

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    With advances in virtual reality technology and its multiple applications, the need for believable, immersive virtual environments is increasing. Even though current computer graphics methods allow us to develop highly realistic virtual worlds, the main element failing to enhance presence is autonomous groups of human inhabitants. A great number of crowd simulation techniques have emerged in the last decade, but critical details in the crowd's movements and appearance do not meet the standards necessary to convince VR participants that they are present in a real crowd. In this paper, we review recent advances in the creation of immersive virtual crowds and discuss areas that require further work to turn these simulations into more fully immersive and believable experiences.Peer ReviewedPostprint (author's final draft

    A practice-led approach to facial animation research

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    In facial expression research, it is well established that certain emotional expressions are universally recognized. Studies into the observer perception of dynamic expressions have built upon this research by highlighting the importance of particular facial regions, timings, and temporal configurations to perception and interpretation. In many studies, the stimuli for such studies have been generated through posing by non-experts or performances by trained actors. However, skilled character animators are capable of crafting recognizable, believable emotional facial expressions as a part of their professional practice. ‘Emotional Avatars’ was conceived as an interdisciplinary research project which would draw upon the knowledge of animation practice and emotional psychology. The aim of the project was to jointly investigate the artistic generation and observer perception of emotional expression animation to determine whether the nuances of emotional facial expression could be artistically choreographed to enhance audience interpretation

    Morphological shape generation through user-controlled group metamorphosis

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    Morphological shape design is interpreted in this paper as a search for new shapes from a particular application domain represented by a set of selected shape instances. This paper proposes a new foundation for morphological shape design and generation. In contrast to existing generative procedures, an approach based on a user-controlled metamorphosis between functionally based shape models is presented. A formulation of the pairwise metamorphosis is proposed with a variety of functions described for the stages of deformation, morphing and offsetting. This formulation is then extended to the metamorphosis between groups of shapes with user-defined, dynamically correlated and weighted feature elements. A practical system was implemented in the form of plugin to Maya and tested by an industrial designer on a group of representative shapes from a particular domain. © 2013 Elsevier Ltd

    Densely connected GCN model for motion prediction

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    © 2020 The Authors. Computer Animation and Virtual Worlds published by John Wiley & Sons, Ltd. Human motion prediction is a fundamental problem in understanding human natural movements. This task is very challenging due to the complex human body constraints and diversity of action types. Due to the human body being a natural graph, graph convolutional network (GCN)-based models perform better than the traditional recurrent neural network (RNN)-based models on modeling the natural spatial and temporal dependencies lying in the motion data. In this paper, we develop the GCN-based models further by adding densely connected links to increase their feature utilizations and address oversmoothing problem. More specifically, the GCN block is used to learn the spatial relationships between the nodes and each feature map of the GCN block propagates directly to every following block as input rather than residual linked. In this way, the spatial dependency of human motion data is exploited more sufficiently and the features of different level of scale are fused more efficiently. Extensive experiments demonstrate our model achieving the state-of-the-art results on CMU dataset

    Sketch-based modeling with a differentiable renderer

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    © 2020 The Authors. Computer Animation and Virtual Worlds published by John Wiley & Sons, Ltd. Sketch-based modeling aims to recover three-dimensional (3D) shape from two-dimensional line drawings. However, due to the sparsity and ambiguity of the sketch, it is extremely challenging for computers to interpret line drawings of physical objects. Most conventional systems are restricted to specific scenarios such as recovering for specific shapes, which are not conducive to generalize. Recent progress of deep learning methods have sparked new ideas for solving computer vision and pattern recognition issues. In this work, we present an end-to-end learning framework to predict 3D shape from line drawings. Our approach is based on a two-steps strategy, it converts the sketch image to its normal image, then recover the 3D shape subsequently. A differentiable renderer is proposed and incorporated into this framework, it allows the integration of the rendering pipeline with neural networks. Experimental results show our method outperforms the state-of-art, which demonstrates that our framework is able to cope with the challenges in single sketch-based 3D shape modeling

    The minimum energy expenditure shortest path method

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    This article discusses the addition of an energy parameter to the shortest path execution process; namely, the energy expenditure by a character during execution of the path. Given a simple environment in which a character has the ability to perform actions related to locomotion, such as walking and stair stepping, current techniques execute the shortest path based on the length of the extracted root trajectory. However, actual humans acting in constrained environments do not plan only according to shortest path criterion, they conceptually measure the path that minimizes the amount of energy expenditure. On this basis, it seems that virtual characters should also execute their paths according to the minimization of actual energy expenditure as well. In this article, a simple method that uses a formula for computing vanadium dioxide (VO2VO_2) levels, which is a proxy for the energy expenditure by humans during various activities, is presented. The presented solution could be beneficial in any situation requiring a sophisticated perspective of the path-execution process. Moreover, it can be implemented in almost every path-planning method that has the ability to measure stepping actions or other actions of a virtual character

    Ambient health monitoring: the smartphone as a body sensor network component

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    Inertial measurement units used in commercial body sensor networks (e.g. animation suits) are inefficient, difficult to use and expensive when adapted for movement science applications concerning medical and sports science. However, due to advances in micro-electro mechanical sensors, these inertial sensors have become ubiquitous in mobile computing technologies such as smartphones. Smartphones generally use inertial sensors to enhance the interface usability. This paper investigates the use of a smartphone’s inertial sensing capability as a component in body sensor networks. It discusses several topics centered on inertial sensing: body sensor networks, smartphone networks and a prototype framework for integrating these and other heterogeneous devices. The proposed solution is a smartphone application that gathers, processes and filters sensor data for the purpose of tracking physical activity. All networking functionality is achieved by Skeletrix, a framework for gathering and organizing motion data in online repositories that are conveniently accessible to researchers, healthcare professionals and medical care workers

    Model Teknokultur Pendidikan Sejarah Indonesia melalui Seni (Studi Kasus: Animasi Pangeran Diponegoro dalam Lukisan Raden Saleh dengan Facial Motion Capture Technology)

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    One potential tool for helping one learn historical thinking and factual knowledge is art. Art can be a powerful tool for engaging people in the process of historical inquiry and for developing their historical thinking. When art is used, one can better understand many perspectives, and also more clearly understand what actually happened in the past. One can gain a wider background knowledge and be more interested in learning history. This study will use digital art as a support tool for history education. Visual construction of Pangeran Diponegoro will be used as a case study. Pangeran Diponegoro in Raden Saleh's painting will be digitized and then animated, and, using motion capture technology, Diponegoro's animation will tell his story to the audience. With this technology, not only historical facts will be delivered, but also the sociocultural aspects during Diponegoro's period will be explained, among other costumes, norms, and habits of the Javanese people. The effectiveness of this experiment will be measured against students in three high schools

    Simulating gaze attention behaviors for crowds

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    Crowd animation is a topic of high interest which offers many challenges. One of the most important is the trade-off between rich, realistic behaviors, and computational costs. To this end, much effort has been put into creating variety in character representation and animation. Nevertheless, one aspect still lacking realism in virtual crowd characters resides in their attention behaviors. In this paper, we propose a framework to add gaze attention behaviors to crowd animations. First, We automatically extract interest points from character or object trajectories in pre-existing animations. For a given character, We assign a set of elementary scores based on parameters such as distance or speed to all other characters or objects in the scene. We then combine these subscores in all overall scoring function. The scores obtained from this function form a set of gaze constraints that determine where and when each character should look. We finally enforce these constraints With all optimized dedicated gaze Inverse Kinematics (IK) solver. It first computes Me displacement maps for the constraints to be satisfied. It then smoothly propagates these displacements over all automatically defined number of frames. We demonstrate the efficiency of our method and our visually convincing results through various examples. Copyright (C) 2009 John Wiley & Sons, Ltd

    Virtual reality training and assessment in laparoscopic rectum surgery

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    Background: Virtual-reality (VR) based simulation techniques offer an efficient and low cost alternative to conventional surgery training. This article describes a VR training and assessment system in laparoscopic rectum surgery. Methods: To give a realistic visual performance of interaction between membrane tissue and surgery tools, a generalized cylinder based collision detection and a multi-layer mass-spring model are presented. A dynamic assessment model is also designed for hierarchy training evaluation. Results: With this simulator, trainees can operate on the virtual rectum with both visual and haptic sensation feedback simultaneously. The system also offers surgeons instructions in real time when improper manipulation happens. The simulator has been tested and evaluated by ten subjects. Conclusions: This prototype system has been verified by colorectal surgeons through a pilot study. They believe the visual performance and the tactile feedback are realistic. It exhibits the potential to effectively improve the surgical skills of trainee surgeons and significantly shorten their learning curve. © 2014 John Wiley & Sons, Ltd
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