• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07a
• /
• pp.682-684
• /
• 2005

본 논문은 인체 스캔 데이터를 예제 데이터베이스로 사용하여 2차원 사진으로부터 3차원 아바타 모델을 생성하는 기술을 제안한다. 직접 기하학적인 변형을 통해 3차원 아바타를 생성하는 기존의 방법들과는 달리, 미리 스캔한 다수의 3차원 인체 형상 모델 데이터베이스를 사용하여 사진에 나타난 실루엣과 가장 일치하도록 기본 모델을 변형 및 계산함으로써 모델을 획득한다. 본 연구는 예제 기반의 모델 변형 방법이 가지는 사실적인 인체 모델 생성의 장점, 2차원 사진을 이용한 방법이 가지는 텍스쳐 매핑 및 실루엣 정보 반영의 장정을 모두 가진다. 변형된 모델은 텍스쳐 매핑을 가한 후 애니메이션을 적용하여 가상환경에 활용할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2005.11a
• /
• pp.809-812
• /
• 2005

본 논문은 원격 교육 환경에서 자료구조 알고리즘을 학습자가 적극적인 상호작용을 통하여 학습자의 이해 능력에 맞추어 학습할 수 있도록 하는 시스템을 소개한다. 기존의 자료구조 알고리즘 학습 시스템들은 고정된 수치 데이터의 애니메이션을 보여주므로 여전히 일방적인 학습이며, 전시되는 예제들의 다양성이 부족하다. 본 시스템에서는 자료의 크기 및 알고리즘 실행속도의 조절과 알고리즘 실행시 코드추적 기능 등의 상호작용을 통하여 알고리즘에 대한 이해를 시각적으로 배가 시킨다. 이 시스템은 웹에서도 지원가능 하도록 플래시 액션스크립트 기반으로 구현하였다.

• Journal of the Korea Computer Graphics Society
• /
• v.28 no.2
• /
• pp.29-41
• /
• 2022

In this paper, we introduce a novel real-time, interactive animation system which uses real-time motion inputs from a low-cost motion-sensing device Kinect. Our system generates interaction motions between the user character and the counterpart character in real-time. While the motion of the user character is generated mimicking the user's input motion, the other character's motion is decided to react to the user avatar's motion. During a pre-processing step, our system analyzes the reference motion data and generates mapping model in advance. At run-time, our system first generates initial poses of two characters and then modifies them so that it could provide plausible interacting behavior. Our experimental results show plausible interacting animations in that the user character performs a modified motion of user input and the counterpart character properly reacts against the user character. The proposed method will be useful for developing real-time interactive animation systems which provide a better immersive experience for users.

• Journal of the Korea Computer Graphics Society
• /
• v.20 no.2
• /
• pp.25-32
• /
• 2014

We present an example-based approach to synthesizing physically simulated Rube Goldberg machines in which a series of rigid body elements are sequentially triggered and driven along the causal chain. Given a set of elements, our goal is to automatically instantiate and arrange those elements to meet the user-specified requirements including the start and end positions, and the boundary of movement. To do so, we first sample small-scale machines consisting of only a few elements randomly, and represent the connectivity between every pair of components as a graph structure. Searching over possible paths in this graph solves our problem by finding a path that can be unrolled to satisfy the given requirements, and then assembling components sequentially along the solution path. In order to ensure that the machine works precisely in a physically simulated environment, we finally elaborate the layout of assembled components by a simple greedy algorithm. We demonstrate the usefulness of our approach by displaying a large diversity of Rube Goldberg machines built with only five kinds of elements.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.3
• /
• pp.133-142
• /
• 2019

In physics-based character animation, trajectory optimization has been widely adopted for automatic motion synthesis, through the prediction of an optimal sequence of future states of the character based on its system dynamics model. In general, the system dynamics model is neither in a closed form nor differentiable when it handles the contact dynamics between a character and the environment with rigid body collisions. Employing smoothed contact dynamics, researchers have suggested efficient trajectory optimization techniques based on numerical differentiation of the resulting system dynamics. However, the numerical derivative of the system dynamics model could be inaccurate unlike its analytical counterpart, which may affect the stability of trajectory optimization. In this paper, we propose a novel method to derive the closed-form derivative for the system dynamics by properly approximating the contact model. Based on the resulting derivatives of the system dynamics model, we also present a model predictive control (MPC)-based motion synthesis framework to robustly control the motion of a biped character according to on-line user input without any example motion data.

• Journal of the Korea Computer Graphics Society
• /
• v.22 no.2
• /
• pp.11-19
• /
• 2016

This paper proposes a method to directly retarget facial motion capture data to the facial rig. Facial rig is an essential tool in the production pipeline, which allows helping the artist to create facial animation. The direct mapping method from the motion capture data to the facial rig provides great convenience because artists are already familiar with the use of a facial rig and the direct mapping produces the mapping results that are ready for the artist's follow-up editing process. However, mapping the motion data into a facial rig is not a trivial task because a facial rig typically has a variety of structures, and therefore it is hard to devise a generalized mapping method for various facial rigs. In this paper, we propose a data-driven approach to the robust mapping from motion capture data to an arbitary facial rig. The results show that our method is intuitive and leads to increased productivity in the creation of facial animation. We also show that our method can retarget the expression successfully to non-human characters which have a very different shape of face from that of human.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.439-444
• /
• 2008

The techniques, which locate example motions in abstract parameter space and interpolate them to generate new motion with given parameters, are widely used in real-time animation system for its controllability and efficiency However, as the dimension of parameter space increases for more complex control, the number of example motions for parameterization increases exponentially. This paper proposes a method that uses two different parameter spaces to obtain decoupled control over upper-body and lower-body motion. At each frame time, each parameterized motion space produces a source frame, which satisfies the constraints involving the corresponding body part. Then, the target frame is synthesized by splicing the upper body of one source frame onto the lower body of the other. To generate corresponding source frames to each other, we present a novel scheme for time-warping. This decoupled parameterization alleviates the problems caused by dimensional complexity of the parameter space and provides users with layered control over the character. However, when the examples are parameterized based on their upper body's spatial properties, the parameters of the examples are varied individually with every change of its lower body. To handle this, we provide an approximation technique to change the positions of the examples rapidly in the parameter space.

• Journal of the Korea Computer Graphics Society
• /
• v.27 no.1
• /
• pp.9-17
• /
• 2021

In this paper, we present a simple and fast supervised learning framework based on model predictive control so as to learn motion controllers for a physic-based character to track given example motions. The proposed framework is composed of two components: training data generation and offline learning. Given an example motion, the former component stochastically controls the character motion with an optimal controller while repeatedly updating the controller for tracking the example motion through model predictive control over a time window from the current state of the character to a near future state. The repeated update of the optimal controller and the stochastic control make it possible to effectively explore various states that the character may have while mimicking the example motion and collect useful training data for supervised learning. Once all the training data is generated, the latter component normalizes the data to remove the disparity for magnitude and units inherent in the data and trains an artificial neural network with a simple architecture for a controller. The experimental results for walking and running motions demonstrate how effectively and fast the proposed framework produces physics-based motion controllers.

• The Journal of the Korea Contents Association
• /
• v.11 no.11
• /
• pp.19-27
• /
• 2011

In this paper, we present an emulation library for the essential features and their API function calls provided by Direct3D, the most actively used API for computer game-related application programs on the MS-Windows-based desktop's, with OpenGL library in the Linux environment. In typical Linux-based systems, only the X window system and OpenGL graphics library are available. There are lots of needs for this kind of emulation library to convert the Direct3D-based game applications and user interfaces on these systems. Through carefully selecting the essential API functions from the DirectX version 9.0, we obtained the prototype implementation of that emulation library, to finally get the final full-scale DirectX implementation. Our implementation currently covers 3D coordinate transformations, light and material processing, texture mapping, simple animation features and more. We showed its feasibility through successfully executing a set of Direct3D demonstration programs including a real-world game character animation on our implementation.