• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.506-508
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• 1999

본 논문에서 제안하는 계층적인 형태의 deformable model을 이용하면 기존의 deformable model 방법이 가지고 있던 여러 문제점을 해결할 수 있다. 특히 가장 큰 문제중의 하나인 초기위치를 찾는 문제나 적용시간이 오래 걸린다는 단점을 상당부분 해결할 수 있다. 또한 계층적인 형태를 사용하면 최종적으로 찾고자 하는 문체가 증가될수록 더 많은 시간상/공간상의 이익을 볼 수 있게 된다. 본 논문에서는 이처럼 계층적인 형태로 deformable model을 구성하는 방법과 계층적 deformable model을 영상에 적용하는 방법, 그리고 그 방법에 대한 공간적/시간적 복잡도 분석을 통해 그 효율성을 알아보았다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4120-4132
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• 2017

In this research, we implement a deformable object simulation system using OpenGL's shader language, GLSL4.3. Deformable object simulation is implemented by using volumetric mass-spring system suitable for real-time simulation among the methods of deformable object simulation. The compute shader in GLSL 4.3 which helps to access the GPU resources, is used to parallelize the operations of existing deformable object simulation systems. The proposed system is implemented using a compute shader for parallel processing and it includes a bounding box-based collision detection solution. In general, the collision detection is one of severe computing bottlenecks in simulation of multiple deformable objects. In order to validate an efficiency of the system, we performed the experiments using the 3D volumetric objects. We compared the performance of multiple deformable object simulations between CPU and GPU to analyze the effectiveness of parallel processing using GLSL. Moreover, we measured the computation time of bounding box-based collision detection to show that collision detection can be processed in real-time. The experiments using 3D volumetric models with 10K faces showed the GPU-based parallel simulation improves performance by 98% over the CPU-based simulation, and the overall steps including collision detection and rendering could be processed in real-time frame rate of 218.11 FPS.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.373-380
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• 2006

Accurate and fast haptic simulations of deformable objects are desired in many applications such as medical virtual reality. In haptic interactions with a coarse model, the number of nodes near the haptic interaction region is too few to generate detailed deformation. Thus, local refinement techniques need to be developed. Many approaches have employed purely geometric subdivision schemes, but they are not proper in describing the deformation behavior of deformable objects. This paper presents a continuum mechanics-based finite element adaptive method to perform haptic interaction 'with a deformable object. This method superimposes a local fine mesh upon a global coarse model, which consists of the entire deformable object. The local mesh and the global mesh are coupled by the s-version finite element method (s-FEM), which is generally used to enhance accurate solutions near the target points even more. The s-FEM can demonstrate a reliable deformation to users in real-time.

• 한국HCI학회:학술대회논문집
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• 2008.02c
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• pp.19-24
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• 2008

This paper presents a physically-based haptic rendering algorithm for a deformable object based on visual information about the intervention between a tool and a real object in a remote place. The physically-based model of a deformable object is created from the mechanical properties of the object and the captured image obtained with a CCD camera. When a slave system exerts manipulation tasks on a deformable object, the reaction force for haptic rendering is computed using boundary element method. Snakes algorithm is used to obtain the geometry information of a deformable object. The proposed haptic rendering algorithm can provide haptic feedback to a user without using a force transducer in a teleoperation system.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.25-33
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• 2023

Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2163-2170
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• 2009

We present an automated, energy minimized-based method for Lung parenchyma segmenting Chest Computed Tomography(CT) datasets. Deformable model is used for energy minimized segmentation. Quantitative knowledge including expected volume, shape of Chest CT provides more feature constrain to diagnosis or surgery operation planning. Segmentation subdivides an lung image into its consistent regions or objects. Depends on energy-minimizing, the level detail image of subdivision is carried. Segmentation should stop when the objects or region of interest in an application have been detected. The deformable model that has attracted the most attention to date is popularly known as snakes. Snakes or deformable contour models represent a special case of the general multidimensional deformable model theory. This is used extensively in computer vision and image processing applications, particularly to locate object boundaries, in the mean time a new type of external force for deformable models, called gradient vector flow(GVF) was introduced by Xu. Our proposed algorithm of deformable model is new external energy of GVF for exact segmentation. In this paper, Clinical material for experiments shows better results of proposal algorithm in Lung parenchyma segmentation on Chest CT.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.559-560
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• 2012

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.780-785
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• 2007

Accurate and fast haptic simulations of deformable objects are desired in many applications such as medical virtual reality. In haptic interactions with a coarse model, the number of nodes near the haptic interaction region is too few to generate detailed deformation. Thus, local refinement techniques need to be developed. Many approaches have employed purely geometric subdivision schemes, but they are not proper in describing the deformation behavior of deformable objects. This paper presents a continuum mechanics-based finite element adaptive method to perform haptic interaction with a deformable object. This method superimposes a local fine mesh upon a global coarse model, which consists of the entire deformable object. The local mesh and the global mesh are coupled by the s-version finite element method (s-FEM), which is generally used to enhance accurate solutions near the target points even more. The s-FEM can demonstrate a reliable deformation to users in real-time.

• Transactions of Materials Processing
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• v.10 no.6
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• pp.478-484
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• 2001

Tube Process (TP) is a process to produce permanent magnets using a deformable tube for densification of magnet powder. This process claims that it can accomplish both densification and anisotropication in one step forming. This process is distinguished from other processes since it uses a deformable copper tube for densification of magnet powder. In this paper, simulation has been carried out for tile Tube Process in a closed die considering the compressibility of powdered material, arbitrary curved shape and deformable body contact between Nd-Fe-B magnet powder and a copper tube. Results show that the finite element analysis of the Tube Process plays an important role in the stage of preform design.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.713-720
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• 2012

Unlike FEM (Finite Element Method), which provides an accurate deformation of soft objects, FFD (Free Form Deformation) based methods have been widely used for a quick and responsive representation of deformable objects in real-time applications such as computer games, animations, or simulations. The FFD-AABB (Free Form Deformation Axis Aligned Bounding Box) algorithm was also suggested to address the collision handling problems between deformable objects at an interactive rate. This paper proposes an enhanced FFD-AABB algorithm to improve the frame rate of simulation by adding the bounding sphere based collision test between 3D deformable objects. We provide a comparative analysis with previous methods and the result of proposed method shows about an 85% performance improvement.