Abstract Extended exposure to virtual reality displays has been linked to the emergence of cybersickness, characterized by symptoms such as nausea, dizziness, fatigue, and disruptions in eye movements. The main objective of our study is to examine the effects of real-time fine-tuning of stereo parameters and blurriness in virtual reality on the discomfort level of users who are experiencing motion sickness triggered by the display. Our hypothesis proposes that by dynamically correcting the rendering settings, the symptoms of motion sickness can be relieved and the overall VR user experience can be improved. Our methodology commences with a prediction model for the comfort level of the viewer based on their gaze parameters, such as pupil diameter, blink count, gaze position, and fixation duration. We then propose a method to dynamically adapt the stereoscopic rendering parameters by considering the predicted comfort level of the viewer.

This work explores a set of well-studied visual saliency features through seven saliency prediction methods with the aim of assessing how applicable they are for estimating visual saliency in dynamic virtual reality (VR) environments that are experienced with head-mounted displays. An in-depth analysis of how the saliency methods that make use of depth cues compare to ones that are based on purely image-based (2D) features is presented. To this end, a user study was conducted to collect gaze data from participants as they were shown the same set of three dynamic scenes in 2D desktop viewing and 3D VR viewing using a head-mounted display. The scenes convey varying visual experiences in terms of contents and range of depth-of-field so that an extensive analysis encompassing a comprehensive array of viewing behaviors could be provided. The results indicate that 2D features matter as much as depth for both viewing conditions, yet depth cue is slightly more important for 3D VR viewing. Furthermore, including depth as an additional cue to the 2D saliency methods improves prediction for both viewing conditions, and the benefit margin is greater in 3D VR viewing.

Abstract Previous studies showed that virtual reality (VR) environments can affect emotional state and cause significant changes in physiological responses. Aside from these effects, inadvertently induced cybersickness is a notorious problem faced in VR. In this study, to further investigate the effects of virtual environments (VEs) with different context, three dynamic VEs were created. Each VE had a particular purpose: evoking no emotion in Campfire (CF), unpleasant emotions in Hospital (HH), and cybersickness symptoms in Roller Coaster (RC). We made use of objective measurements of physiological responses such as pupil dilation, blinks, fixations, saccades, and heart rate, as well as subjective self‐assessments via pre‐ and post‐VE session questionnaires. While previous studies investigate different subsets of these measures, our study makes a comprehensive analysis of them jointly in dynamic VEs. The results of the study indicate that cybersickness produced higher saccade mean speed, whereas unpleasant context caused higher fixation count, saccade rate, and pupil dilation. Moreover, CF decreased anxiety, whereas HH and RC increased it and they also decreased comfort. Participants felt cybersickness in all VEs even in CF which is designed to minimize the effects.

Abstract Providing multiple meanings in a single piece of art has always been intriguing to both artists and observers. We present Purkinje images, which have different interpretations depending on the luminance adaptation of the observer. Finding such images is an optimization that minimizes the sum of the distance to one reference image in photopic conditions and the distance to another reference image in scotopic conditions. To model the shift of image perception between day and night vision, we decompose the input images into a Laplacian pyramid. Distances under different observation conditions in this representation are independent between pyramid levels and pixel positions and become matrix multiplications. The optimal pixel colour can be found by inverting a small, per‐pixel linear system in real time on a GPU. Finally, two user studies analyze our results in terms of the recognition performance and fidelity with respect to the reference images.

Abstract We present a novel method for retargeting human motion to arbitrary 3D mesh models with as little user interaction as possible. Traditional motion‐retargeting systems try to preserve the original motion, while satisfying several motion constraints. Our method uses a few pose‐to‐pose examples provided by the user to extract the desired semantics behind the retargeting process while not limiting the transfer to being only literal. Thus, mesh models with different structures and/or motion semantics from humanoid skeletons become possible targets. Also considering the fact that most publicly available mesh models lack additional structure (e.g. skeleton), our method dispenses with the need for such a structure by means of a built‐in surface‐based deformation system. As deformation for animation purposes may require non‐rigid behaviour, we augment existing rigid deformation approaches to provide volume‐preserving and squash‐and‐stretch deformations. We demonstrate our approach on well‐known mesh models along with several publicly available motion‐capture sequences.

Abstract Learned biomechanical strategies prepare the human body in kinematics and kinetics terms during interception tasks, such as throwing and catching, in real world. Based on this, we present a real‐time physics‐based approach that generates natural and physically plausible motions for a highly complex task ball catching. We showed that ball catching behavior could be achieved with the proper combination of rather simple motor skills, such as standing, walking, and reaching. The character learns some policies to know how and when to react by using reinforcement learning in order to use time accurately. We demonstrate the effectiveness of our method with some of the catching animation results in different catching strategies. Copyright © 2015 John Wiley & Sons, Ltd.

ABSTRACT Human body movements and postures carry emotion‐specific information. On the basis of this motivation, the objective of this study is to analyze this information in the spatial and temporal structure of the motion capture data and extract features that are indicative of certain emotions in terms of affective state descriptors. Our contribution comprises identifying the directly or indirectly related descriptors to emotion classification in human motion and conducting a comprehensive analysis of these descriptors (features) that fall into three different categories: posture descriptors, dynamic descriptors, and frequency‐based descriptors in order to measure their performance with respect to predicting the affective state of an input motion. The classification results demonstrate that no single category is sufficient by itself; the best prediction performance is achieved when all categories are combined. Copyright © 2013 John Wiley & Sons, Ltd.

This special issue contains 28 papers selected from the Computer Animation and Social Agents 2013 (CASA'2013) Conference. This conference was founded by the Computer Graphics Society in 1988 in Geneva and has, since then, been held in various countries around the world, 2011 in China, last year in Singapore, this year in Istanbul, Turkey, and next year in Houston, USA. The 3-day conference features more than 55 speakers who present their most current research in the areas of computer animation, autonomous social robots and virtual humans, and how these technologies can be leveraged to advance related areas, such as music, virtual cities, and crowd control. Addressing this year's conference are human motion modeling expert associate professor Jinxiang Chai from Texas A&M University and renowned haptics researcher, associate professor Cagatay Basdogan of Koc University. This year, we received 141 full papers and selected only 28 of those for this special issue; meaning, an acceptance rate of only 20%. It is needless to say that these are of high quality, all having been reviewed by at least three reviewers. The themes are various, covering the entire international field of research in computer animation and virtual worlds and sorted by their sessions in the conference; they are as follows. Crowd Simulation, Fluid Simulation, Natural Phenomena and Lighting, Face/Hair Animation and Rendering, Virtual Cities and Path Planning, Paint Simulation, Medical/Immersive Applications, Virtual Agents, 3D Mesh Deformation, Human Action Recognition, 3D Mesh and Geometric Modeling, and Human Motion. We would like to thank the authors for having submitted a paper to CASA'2013 as well as the Program Committee members, the external reviewers, and all the people who have contributed to the success of CASA 2013 in Istanbul. Nadia Magnenat-Thalmann Mustafa Kasap Daniel Thalmann Tolga Capin Selim Balcisoy Tolga Eren Norman Badler Selim Balcisoy Ronan Boulic Yiyu Cai Tolga Capin Marc Cavazza Bing-Yu Chen Yiorgos Chrysanthou Sabine Coquillart Frederic Cordier Justin Dauwels Etienne De-Sevin Zhi-Gang Deng Fabian Di Fiore Yves Duthen Arjan Egges Abdennour El Rhalibi Petros Faloutsos Ugur Gudukbay Mario Gutierrez James Hahn Ying He Shi-Min Hu Zhiyong Huang Veysi Isler Jean-Pierre Jessel Sophie Joerg Chris Joslin Prem Kalra Mustafa Kasap Scott King Taku Komura Caroline Larboulette Rynson Lau Wonsook Lee Tsai-Yen Li Ming Lin Anderson Maciel Nadia Magnenat Thalmann Dinesh Manocha Rachel Mcdonnell Franck Multon Soraia Musse Junyong Noh Igor Pandzic George Papagiannakis Laura Papaleo Nuria Pelechano Christopher Peters Julien Pettre Flavien Picon Tiberiu Popa Nicolas Pronost Isaac Rudomin Hyewon Seo Hubert Shum Matthias Teschner Daniel Thalmann Xin Tong Andy W. H. Khong Huamin Wang Jun Wang Enhua Wu Junsong Yuan Cem Yuksel Zerrin Yumak Jian Zhang Zhengyou Zhang Jianmin Zheng

During the visualization of 3D content, using the depth cues selectively to support the design goals and enabling a user to perceive the spatial relationships between the objects are important concerns. In this novel solution, we automate this process by proposing a framework that determines important depth cues for the input scene and the rendering methods to provide these cues. While determining the importance of the cues, we consider the user's tasks and the scene's spatial layout. The importance of each depth cue is calculated using a fuzzy logic--based decision system. Then, suitable rendering methods that provide the important cues are selected by performing a cost-profit analysis on the rendering costs of the methods and their contribution to depth perception. Possible cue conflicts are considered and handled in the system. We also provide formal experimental studies designed for several visualization tasks. A statistical analysis of the experiments verifies the success of our framework.

Abstract Motion capture is an increasingly popular animation technique; however data acquired by motion capture can become substantial. This makes it difficult to use motion capture data in a number of applications, such as motion editing, motion understanding, automatic motion summarization, motion thumbnail generation, or motion database search and retrieval. To overcome this limitation, we propose an automatic approach to extract keyframes from a motion capture sequence. We treat the input sequence as motion curves, and obtain the most salient parts of these curves using a new proposed metric, called 'motion saliency'. We select the curves to be analysed by a dimension reduction technique, Principal Component Analysis (PCA). We then apply frame reduction techniques to extract the most important frames as keyframes of the motion. With this approach, around 8% of the frames are selected to be keyframes for motion capture sequences. Copyright © 2010 John Wiley & Sons, Ltd.

This paper aims at providing an overview of the core technologies enabling the delivery of 3-D Media to next-generation mobile devices. To succeed in the design of the corresponding system, a profound knowledge about the human visual system and the visual cues that form the perception of depth, combined with understanding of the user requirements for designing user experience for mobile 3-D media, are required. These aspects are addressed first and related with the critical parts of the generic system within a novel user-centered research framework. Next-generation mobile devices are characterized through their portable 3-D displays, as those are considered critical for enabling a genuine 3-D experience on mobiles. Quality of 3-D content is emphasized as the most important factor for the adoption of the new technology. Quality is characterized through the most typical, 3-D-specific visual artifacts on portable 3-D displays and through subjective tests addressing the acceptance and satisfaction of different 3-D video representation, coding, and transmission methods. An emphasis is put on 3-D video broadcast over digital video broadcasting-handheld (DVB-H) in order to illustrate the importance of the joint source-channel optimization of 3-D video for its efficient compression and robust transmission over error-prone channels. The comparative results obtained identify the best coding and transmission approaches and enlighten the interaction between video quality and depth perception along with the influence of the context of media use. Finally, the paper speculates on the role and place of 3-D multimedia mobile devices in the future internet continuum involving the users in cocreation and refining of rich 3-D media content.

'Rich media' is a term that implies the integration of all of the advances we have made in the mobile space delivering music, speech, text, graphics and video. This is true, but it is more than the sum of its parts. Rich media is the ability to deliver these modalities, to interact with these modalities, and to do it in a way that allows for the construction, delivery and use of compelling mobile services in an effective and economic manner. In this paper, we introduce a system called mobile open rich-media environment ('MORE') that helps realize such mobile rich media services, combining various technologies of W3C, OMA, 3GPP and IETF standards. The different components of the system include formatting, packaging, transporting, rendering and interacting with rich media files and streams

In this paper, we present an approach for facilitating user interaction on mobile devices, focusing on camera-enabled mobile phones. A user interacts with an application by moving their device. An on-board camera is used to capture incoming video and the scrolling direction and magnitude are estimated using a computer vision-based algorithm. The direction is used as the scroll direction in the application, and the magnitude is used to set the zoom level. The camera is treated as a pointing device and zoom level control in applications. Our approach generates mouse events, so any application that is mouse-driven can make use of this technique. The user is free to browse through large data sets on a limited size display with one hand, ideal for the mobile domain.

In networked virtual environments (NVEs), users are represented by their virtual embodiments. The articulated structure of these embodiments introduces a new complexity in the representation and streaming of animations, especially when the number of participants in the simulation increases. This requires real-time algorithms to decrease the networking overhead. The dead-reckoning technique is a way to reduce the required bit rate, and has been used for simple nonarticulated objects in popular NVE systems. We introduce a dead-reckoning technique for articulated virtual human figures, based on the MPEG-4 body animation specification, using Kalman filtering.

Integrating virtual human animation in networked virtual environments (NVEs) has the potential to create severe network load issues. In NVEs, users are represented by their virtual embodiments. The articulated structure of these embodiments introduces a new complexity in the communication, representation and streaming of animations. This might create a significant overhead, especially as the number of participants in the simulation increases. In this paper, we present problems and solutions to efficiently transmit virtual human data over the network.

Introducing seemingly autonomous virtual beings into virtual environments to co-habit and collaborate with us is a continuous challenge and source of interest. Latest proof of human excitement for virtual life is the current worldwide craze for electronic pets that must be fed and cared for lest they develop a bad character or die. Even more interesting is the inclusion of autonomous actors in networked collaborative virtual environments (NCVEs). They provide a meeting place for people from different geographical locations and virtual beings. In NCVEs one doesn't see correspondents, only their graphical representations in the virtual world, which is the same as for the virtual ones-therefore the communication with virtual beings can come naturally. There is no single solution to the simulation of autonomous behavior. This is an ongoing research topic. Therefore it is interesting to provide an open NCVE system for easy interfacing with various implementations of autonomous behavior. In this way, the system can serve as an application platform with existing algorithms, as well as a research testbed for new autonomous behavior algorithms. The paper studies the requirements for such an open interface and, based on this study, presents an implementation within the Virtual Life Network (VLNET) system. Results are presented in terms of two case studies. A simple one implementing a dumb servant character and a more complex one connecting VLNET with the autonomous agent program Eliza (Weizenbaum, 1966).

This paper presents a crowd modelling method in Collaborative Virtual Environment (CVE) which aims to create a sense of group presence to provide a more realistic virtual world. An adaptive display is also presented as a key element to optimise the needed information to keep an acceptable frame rate during crowd visualisation. This system has been integrated in the several CVE platforms which will be presented at the end of this paper. 1.1 Keywords Autonomous agents, virtual crowds, virtual environments.

Navigation within the scope of a Networked Collaborative Virtual Environment (NCVE) using an articulated body representation is mores complex then just moving the viewpoint based on user input.In such context, navigation englobes problems such as mapping of user's actions on the embodiment and body constraints in addition to the usual ones such as universal support for different devices and global motion constraints.We take a broader look at the problems, clasify them and present a solution for navigation in NCVEs.Basic navigation involves using some input device to control walk-through or fly-through motion.In the context

Complex virtual human representation provides more natural interaction and communication among participants in networked virtual environments, hence it is expected to increase the sense of being together within the same virtual world. We present a flexible framework for the integration of virtual humans in networked collaborative virtual environments. A modular architecture allows flexible representation and control of the virtual humans, whether they are controlled by a physical user using all sorts of tracking and other devices, or by an intelligent control program turning them into autonomous actors. The modularity of the system allows for fairly easy extensions and integration with new techniques making it interesting also as a testbed for various domains from “classic” VR to psychological experiments. We present results in terms of functionalities, example applications and measurements of performance and network traffic with an increasing number of participants in the simulation.

Abstract We describe the HUMANOID environment dedicated to human modeling and animation for general multimedia, VR, and CAD applications integrating virtual humans. We present the design of the system and the integration of the various features: generic modeling of a large class of entities with the BODY data structure, realistic skin deformation for body and hands, facial animation, collision detection, integrated motion control and parallelization of computation intensive tasks.