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This journal subline serves as a forum for stimulating and disseminating innovative research ideas, theories, emerging technologies, empirical investigations, state-of-the-art methods, and tools in all different genres of edutainment, such as game-based learning and serious games, interactive storytelling, virtual learning environments, VR-based education, and related fields. It covers aspects from educational and game theories, human-computer interaction, computer graphics, artificial intelligence, and systems design. The 6th volume in this series represents a selection of 7 contributions from DMDCM 2011, the 5th International Conference on Digital Media and Digital Content Management, held in Chongqing, China, in December 2011, as well as 18 contributions from CASA 2011, the 24th International Conference on Computer Animation and Social Agents, held in Chengdu, China, in May 2011. The topics covered are: pen-based interface, urban heat island simulation, BR-based on-line expo, physically-based tree animation, 3D face texture stitching, chessboard corner extraction, textured-based tracking, motion control, motion capture and retargeting, path planning, physics based animation, image based animation, behavioral animation, artificial life, deformation, facial animation, multi-resolution and multi-scale models, knowledge-based animation, motion synthesis; social agents and avatars, emotion and personality, virtual humans, autonomous actors, AI based animation, social and conversational agents, inter-agent communication, social behavior, gesture generation, crowd simulation; animation compression and transmission, semantics and ontologies for virtual humans and virtual environments, animation analysis and structuring, anthropometric virtual human models, acquisition and reconstruction of animation data, level of details, semantic representation of motion and animation, medical simulation, cultural heritage, interaction for virtual humans, augmented reality and virtual reality, computer games and online virtual worlds.



Digital Media and Digital Content Management (Papers from DMDCM 2010)

Prediction and Visualization for Urban Heat Island Simulation

The simulation and forecast of urban heat island effect was studied. Since the reason for the formation of urban heat island is complex, the current model cannot take all the influence factors into consideration. When a new influence factor is introduced, it will lead to a comprehensive change of the model. In order to solve these problems, the paper provides an urban heat island effect analysis and forecast model based on artificial neural network. The experiment shows the efficiency of this forecast model. Furthermore, the heat island effect information visualization has been carried on in this paper. This prediction model for urban heat island has raised a new idea for the latest achievements of computer technology applications in related fields.
Bin Shao, Mingmin Zhang, Qingfeng Mi, Nan Xiang

Architecture Design and Avatar Customization of On-Line Expo

The On-line Expo is one of the highlights of Shanghai Expo in 2010. It presents the content of real Expo in 3D forms with the help of Internet, multimedia and virtual reality, constructing a virtual environment or platform between visitors and Expo, allowing people to access the on-line Expo in anytime anywhere. In this paper, we first discuss the architecture of the on-line Expo, and then describe the design and implementation of avatar customization. With this method, the system can create the 3D face for avatars based on the input of one front picture of the user without any interaction..
Zheng Li, Nan Xiang, Ruiying Jiang, Cailiang Shen

3D Face Texture Stitching Based on Differential Coordinates

In this paper, we present a new method for 3D face texture stitching based on Differential Coordinates in which 3D texture patch from different face samples can be seamless stitched patch together. Usually, traditional stitching methods for geometric textures involve two works: stitching on shape and stitching on textures. None of them combine these two works. 3D face model is composed of two parts information: surface geometry and texture elements. A natural and realistic face model can be created by interactions between them. So, the approach presented in this paper can get good result. We demonstrate that our approach enables to edit texture elements while considering the shape of face sample.
Yun Ge, Baocai Yin, Yanfeng sun, Hengliang Tang

Physically-Based Tree Animation and Leaf Deformation Using CUDA in Real-Time

This paper presents a novel physically-based parallel approach to animate tree motion in realtime and the leaf deformation is accelerated on a CUDA-based platform. Since physically-based tree animation can hardly achieve realtime performance due to the complicated geometry and expensive calculation. Therefore in this paper, three main measures are taken to overcome this problem. Firstly, we briefly introduce a method of physically-based tree motion called hierarchical matrix structure model driven by the external forces such as the wind; then we analyze the model on a parallel platform in detail; finally, all the tree data structures will be redefined as arrays which are suitable for parallel implementation on GPU. In addition, leaf deformation with a double layer structure, caused by its internal forces, will also be well mapped from CPU to GPU using a similar parallel mechanism. Experimental results show that many species of trees can animate realistically and naturally in realtime; Meanwhile, leaf deformation can be plausibly simulated and the performance will be improved by up to ten times.
Meng Yang, Meng-cheng Huang, En-hua Wu

Simulation of Implosion and Transportation of Ore in Digital Mine

Digital mining technology and software development are essential for informatization in China coal industry. We adopt .net3.0 platform and OpenGL graphics library to develop a system to simulate the process of ore’s implosion and the process of ore’s transportation. In order to implement these functions, the particle system principle and some physical algorithms are used in this system. Besides, other additional functions such as scenes navigating and data statistics are included. Experimental results show that this system can dynamic simulate excavation situations in different mines and has high application value.
Xixi Huang, Dongyong Yan, Fuli Wu, Nan Xiang, Mingmin Zhang

An Automatic and Robust Chessboard Corner Extraction

Camera calibration is crucial in many applications. Our lab uses the world wide used camera calibration toolbox for Matlab and finds its two major drawbacks, i.e., manual selection of the four extreme corners and inability to process images larger than 2MP. In this paper, a new method to eliminate these drawbacks is presented. The original chessboard is modified slightly and based on the added boundary composed of four narrow rectangles, the four extreme corners can be forecast. In addition, because it is implemented by C++, the 2MP limitation no longer exists. The experiment shows that even without multithread optimization and even for a 50MP photo, the corners can be extracted within 20 seconds on a 3GHz CPU.
Xifan Shi, Ning Hong, Tiefeng Cai

An Adaptive Gradient Enhanced Texture Based Tracking Algorithm for Video Monitoring Applications

Object tracking is an important technology in video surveillance. The main approach is Mean Shift algorithm and its improved version. Studies show that the traditional Mean Shift algorithm adopts a fixed searching window in the tracking process, which cannot adjust the template adaptively. The improved algorithm, CamShift, overcomes this problem with an adaptively changing searching window. However, these algorithms are both based on color tracking, which requires that the colors of the foreground targets are unique. If the color of the target is similar to the color of the background, tracking errors will occur or tracking targets will be lost. In this study, we developed an adaptive gradient enhanced texture based tracking algorithm for traffic monitoring applications. This algorithm combines the characteristics of the color and texture of objects. The algorithm builds a joint histogram template of color and texture for targeting, which solves the problems of tracking targets losing when the color of the object is similar to the color of the background. The experiments show that the algorithm can improve the accuracy and robustness of object tracking.
Huibin Wang, Xuewen Wu, Rong Hong

Computer Animation and Social Agents (Papers from CASA 2011)

A Novel Method for Large Crowd Flow

Large scale crowd simulation can be difficult using existing techniques due to the high computational cost of the update to large number of crowd. We present a novel technique for simulating detailed groups quickly. Coarse grid is used to represent the macroscopic crowd distribution and motion tendency consistent with fluid dynamics, allowing for a fast implicit update to a few agents for local path planning and Congestion Avoidance. This allows our simulations to run at a fraction of the cost of existing techniques while still providing the fine scale structure and details obtained. Our method scales well to very large crowd and is suitable to dynamically changing environment.
Xiaoxi He, Leiting Chen, Qingxin Zhu

Evoking Panic in Crowd Simulation

In order to exhibit panic phenomenon in the crowd simulation, special rules or parameters setting is needed for a given scene. In this paper, we present a panic model, named PPIB (Panic, Propagation and Influence on Behavior), which could evoke panic automatically under dangerous situation without manual intervention. PPIB describes panic behavior in three perspectives, including human mental factors and their variation caused by local situation, panic propagation, and influence of panic over the basic factors of pedestrian dynamic. Experiments show that combined with a dynamical crowd model, PPIB could evoke a wide variety of panic behaviors and exhibit emergent phenomena in crowd simulation.
Tianlu Mao, Qing Ye, Hao Jiang, Shihong Xia, Zhaoqi Wang

A Behavior Model Based On Information Transmission for Crowd Simulation

In this paper, a crowd behavior model based on information transmission processes is presented. In crowds, human behaviors are easily influenced by information. The information is transferred to them by other people and surrounding environment. When emergencies occur in crowds, people get danger information when they see an emergency occurs or other people tell them. People in the crowd are intelligent agents. They get information from their surroundings, make decisions according to certain events and take some actions according to the decisions. The contribution of this paper would be that information transmission processes is used and taken into account by the agents. This behavior model can simulate how information about danger is transferred in crowd in emergency situations. By combining the information transmission processes with people’s personalities, it can achieve good crowd evacuation simulation.
Ting Dong, Yan Liu, Lin Bian

Pattern Based Motion for Crowd Simulation

We present a pattern-based approach for simulating the steering behaviour of pedestrians, which aims to imitate the way that real pedestrians perceive spatial-temporal information and make steering decisions in daily-life situations. Novel representations of spatial-temporal patterns are proposed that allow modellers to intuitively and naturally specify some prototypical patterns for various steering behaviours. Based on the spatial-temporal patterns, a hierarchical pattern matching process has been developed, which simulates how pedestrians process spatial temporal information and make steering decisions. Experimental results show that this new approach is quite promising and capable of producing human-like steering. We hope that the idea presented in this paper can direct researchers in this area with a fresh perspective.
Nan Hu, Michael Lees, Suiping Zhou, Vaisagh Viswanathan T.

Adding Physical Like Reaction Effects to Skeleton-Based Animations Using Controllable Pendulums

We propose a system capable in real time of adding controllable and plausible oscillating physical like reaction effects in response to external forces (perturbations). These oscillating effects may be used to modify a motion or to customize it in a cartoon like way. The core of our system is based on several connected 3D pendulums with a propagating reaction. These pendulums always return to a preferred direction that can be fixed in advance or can be modified during the motion by external predefined data (such as keyframe). Our pendulums are fully controllable, concerning reaction time and damping, and the results are completely deterministic. They are easy to implement, even without any prior knowledge of physical simulations. Our system is applicable on articulated body with predefined motion data (manually set or captured) or procedural animation.
Ahmad Abdul Karim, Thibaut Gaudin, Alexandre Meyer, Axel Buendia, Saida Bouakaz

Movement Classes from Human Motion Data

We present a new method for identifying a set of movement types from unlabelled human motion data. One typical approach first segments input motion into a series of intervals, and then clusters those into a set of groups. Unfortunately, the dependency between segmentation and clustering causes trouble in alternate tuning of parameters. Instead, we unify those two tasks in a single optimization framework that searches for the optimal segmentation maximizing the quality of clustering. The genetic algorithm is employed to address this combinatorial problem with our own genetic representation and fitness function. As the primary benefit, the user is able to obtain a repertoir of major movements just by selecting the number of classses to be identified. We demonstrate the usefulness of our approach by providing visual descriptions of motion data, and an intuitive animation authoring interface based on movement collections.
Kang Hoon Lee, Jong Pil Park, Jehee Lee

Front View vs. Side View of Facial and Postural Expressions of Emotions in a Virtual Character

In 3D virtual environments and social scenes, virtual characters are not always visible from a front view. Nonverbal expressions of emotions should be designed so as to be properly perceived when viewed from multiple angles. Our platform enables the design of facial expressions including 3D expressive wrinkles and 3D postures. It was used to generate stimuli for studying the impact of front versus side views on the perception of blends of facial and postural expressions of emotions. Results observed in previous studies for front views of incongruent images are confirmed for side views. Furthermore, subjects were less confident in their ratings for side views images than for front view images.
Matthieu Courgeon, Céline Clavel, Ning Tan, Jean-Claude Martin

Evaluating Emotional Content of Acted and Algorithmically Modified Motions

Motion capture is a common method to create expressive motions for animated characters. In order to add flexibility when reusing motion data, many ways to modify its style have been developed. However, thorough evaluation of the resulting motions is often omitted. In this paper we present a questionnaire based method for evaluating visible emotions and styles in animated motion, and a set of algorithmic modifications to add emotional content to captured motion. Modifications were done by adjusting posture, motion path lengths and timings. The evaluation method was then applied to a set of acted and modified motions. The results show that a simple questionnaire is a useful tool to compare motions, and that expressivity of some emotions can be controlled by the proposed algorithms. However, we also found that motions should be evaluated using several describing dimensions simultaneously, as a single modification may have complex visible effects on the motion.
Klaus Lehtonen, Tapio Takala

An Emotion Model for Virtual Agents with Evolvable Motivation

Modeling emotion for virtual agents is an interesting topic in virtual reality; autonomous virtual agents with emotion can enhance the authenticity of a virtual environment. Motivation and personality are psychological parameters for a virtual agent, motivation is the direct cause to promote an agent’s emotion and behaviors, and an emotion model for virtual agents should include motivations. A computational emotion model for virtual agents with evolvable motivation is presented. First, a virtual agent’s architecture that integrates emotion and motivation is proposed. Second, a fuzzy inference based emotion model with the consideration of personality and motivation is set up, a motivation priority evolves by genetic algorithms. Finally, an experiment is realized to verify effectiveness of the model.
Zhen Liu, Yuan Hong, Qiong Liu, Yan Jie Chai

Sketch-Based Skeleton-Driven 2D Animation and Motion Capture

We present a novel sketch-based 2D animation technique, which allows the user to produce 2D character animations efficiently. It consists of two parts, sketch-based skeleton-driven 2D animation production and 2D motion capture. The user inputs one image of the character and sketches the skeleton for each subsequent frame. The system deforms the character and creates animations automatically. To perform 2D shape deformation, a variable-length needle model is introduced to divide the deformation into two stages: skeleton driven deformation and nonlinear deformation in joint areas. It preserves the local geometric features and global area. Compared with existing approaches, it reduces the computation complexity and produces plausible results. Because our technique is skeleton-driven, the motion of character can be captured by tracking joints position and retargeted to a new character. This facilitates the reuse of motion characteristics contained in existing moving images, making the cartoon generation easy for artists and novices alike.
Junjun Pan, Jian J. Zhang

A Multi-layer Model for Face Aging Simulation

Face aging simulation is a very complex and challenging task and interests many researchers in the fields of psychology, computer graphics and computer vision due to its widely applications. In this paper, we propose a multi-layer coarse-to-fine face representation and aging simulation and animation algorithm. In the coarse layer, we build a global statistical appearance model for representation and faces are aged based on the learned age trajectory in the appearance space. In the mid layer, we learned a set of age specific coupled dictionaries and the faces are represented and aged via the sparse representation on the learned dictionary. At the fine layer, we sample a lot of patches of facial components and skin zones from images of each age group and use them as the dictionaries to simulate the aging effects of the facial components and wrinkles. We collect a database of 10,050 Chinese passport-type images with different ages for the learning and aging simulation. Experimental results demonstrate the effectiveness of the proposed method.
Yixiong Liang, Ying Xu, Lingbo Liu, Shenghui Liao, Beiji Zou

Particle-Based Fracture Simulation on the GPU

In this paper, a particle-based framework is presented to simulate the fracture phenomenon in computer graphics field. First, the object is represented as discrete particles, and then we introduce the Extend Discrete Element Method (EDEM) simulation to describe the interactions between neighbouring particles based on the material mechanics analysis. To process the fracture, a reverse idea to traditional method is used to cooperate with auxiliary cone algorithm, which called anti-fracture mechanism. The physical computation is executed on the GPU with CUDA and a uniform grid data structure is used in order to search the neighbouring element effectively. Experiment results demonstrate the feasibility and effectiveness of our method.
Jiangfan Ning, Huaxun Xu, Liang Zeng, Sikun Li

Mining Subsidence Prediction Based on 3D Stratigraphic Model and Visualization

3D phenomenon involved in mining subsidence was Classified, summarized and aggregated, established the hierarchical structure that describing the geologic phenomena and engineering phenomena of stratum structure. Proposed a 3D stratigraphic model that mixed Multi-DEM with Tetrahedral Network. The model uses Multi-DEM to build layered surface of the earth’s surface and geology, and uses TEN to makeup inter layer geological mass. This is in favor of exactly expressing the surface information, and it is benefit to engineers and technicians to check the geological condition in the stratum, also it provides detailed geological mining conditions for the mining subsidence prediction research and accurately establishes prediction model. Engineering sample shows that the predicted results of the system is more close to the measured values.
Ruisheng Jia, Yanjun Peng, Hongmei Sun

Detail-Preserving Rendering of Free Surface Fluid with Lattice Boltzmann

Free surface flows represent a special case in the fluids simulation application. A highly effective method of modeling and rendering based on Lattice Boltzmann Model (LBM) to simulate the fluid with free surface is presented. Firstly, the LBM model with adaptive coarsening grids for free surface flows is adopted to model the fluid volume. And then a new method combined with the Marching Cubes and free surface algorithm is proposed to extract the fluid surface. Adaptive surface tension combining wave particles equation is used to show the details of fluid surface. After that, an external stack mechanism of moving obstacles is used to realize interacting calculation of fluid with environment. Finally, the hardware accelerating technology is successfully adopted to achieve realistic rendering of complex fluid scenes with different free surface, including flush flood, droplet, etc.
Changbo Wang, Qiang Zhang, Zhuopeng Zhang, Peng Yang, Zhengdong Xia

A Human Action Recognition Algorithm Based on Semi-supervised Kmeans Clustering

This paper proposes a new method of semi-supervised human action recognition. In our approach, the motion energy image(MEI) and motion history image(MHI) are firstly used as the feature representation of the human action. Then, the constrained semi-supervised kmeans clustering algorithm is utilized to predict the class label of unlabeled training example. Meanwhile the average motion energy and history images are calculated as the recognition model for each category action. The category of the observed action is determined according to the correlation coefficients between its feature images and the pre-established average templates. The experiments on Weizmann dataset demonstrate that our method is effective and the average recognition accuracy can reach above 90% even when only using very small number of labeled action sequences.
Hejin Yuan, Cuiru Wang

A New Region Growing Algorithm for Triangular Mesh Recovery from Scattered 3D Points

A novel region growing algorithm is proposed for triangular mesh recovery from scattered 3D points. In our method, the new principle is used to determine the seed triangle considering both maximum angle and minimum length; the open influence region is defined for the active edge under processing; positional element is added into the criterion to choose the most suitable active point; geometric integrity is maintained by analyzing different situations of the selected active point and their corresponding treatments. Our approach has been tested with various unorganized point clouds, and the experimental results proved its efficiency in both accuracy and speed. Compared with the existing similar techniques, our algorithm has the ability to recover triangular meshes while preserving better topological coherence with the original 3D points.
Chengjiang Long, Jianhui Zhao, Ravindra S. Goonetilleke, Shuping Xiong, Yihua Ding, Zhiyong Yuan, Yuanyuan Zhang

Detecting Moving Targets from Traffic Video Based on the Dynamic Background Model

An efficient method to detect the moving target in traffic video based on the dynamic background model is proposed in this paper, after analyzing existing methods for target detection. The model of target detection is given firstly, then a rough set weighted classification method for video image is presented. Based on the video classifications, the background model is established on the historical data. The background judgment and moving object detection for video are done with this model and then the background model is updated with the current video. The experimental results show that this method can adapt the diversification of background and has high adaptability and precision. The processing speed can meet the requirement of real time detection.
Bin Shao, Yunliang Jiang, Qing Shen

Real-Time Implementation for Weighted-Least-Squares-Based Edge-Preserving Decomposition and Its Applications

This paper presents a GPU-based implementation for constructing edge-preserving multiscale image decompositions. An input image is decomposed into a piecewise smooth base layer and multiple detail layers. The base layer captures large scale variations in the image, while the detail layers contain the small scale details. The detail layers are progressively obtained with the edge-preserving weighted least squares optimizations. The improvement of performance is achieved by introducing a Jacobi-like GPU solver, which converges to the right solution much faster than the standard Jacobi iterator. Note that the whole pipeline design is highly parallel, enabling a real-time implementation. Several experimental examples on edge-preserving tonal adjustment and image abstraction are shown to demonstrate the feasibility of the proposed method.
Qingfeng Li, Hanli Zhao


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