• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.66-71
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• 2019

In shape from focus (SFF) methods, the quality of image focus volume plays a vital role in the quality of 3D shape reconstruction. Traditionally, a linear 2D filter is applied to each slice of the image focus volume to rectify the noisy focus measurements. However, this approach is problematic because it also modifies the accurate focus measurements that should ideally remain intact. Therefore, in this paper, we propose to enhance the focus volume adaptively by applying 3-dimensional weighted least squares (3D-WLS) based regularization. We estimate regularization weights from the guidance volume extracted from the image sequences. To solve 3D-WLS optimization problem efficiently, we apply a technique to solve a series of 1D linear sub-problems. Experiments conducted on synthetic and real image sequences demonstrate that the proposed method effectively enhances the image focus volume, ultimately improving the quality of reconstructed shape.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.27-37
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• 2008

Applications of 3D data increase with advancement of multimedia technique and contents, and it is necessary to manage and to retrieve for 3D data efficiently. In this paper, we propose a new method using the sliced shape which extracts efficiently a feature description for shape-based retrieval of 3D models. Since the feature descriptor of 3D model should be invariant to translation, rotation and scale for its model, normalization of models requires for 3D model retrieval system. This paper uses principal component analysis(PCA) method in order to normalize all the models. The proposed algorithm finds a direction of each axis by the PCA and creates orthogonal n planes in each axis. These planes are orthogonalized with each axis, and are used to extract sliced shape image. Sliced shape image is the 2D plane created by intersecting at between 3D model and these planes. The proposed feature descriptor is a distribution of Euclidean distances from center point of sliced shape image to its outline. A performed evaluation is used for average of the normalize modified retrieval rank(ANMRR) with a standard evaluation from MPEG-7. In our experimental results, we demonstrate that the proposed method is an efficient 3D model retrieval.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.1006-1011
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• 2007

Active Appearance Models은 객체의 모델링에 널리 사용되며, 특히 얼굴 모델은 얼굴 추적, 포즈 인식, 표정 인식, 그리고 얼굴 인식에 널리 사용되고 있다. 최초의 AAM은 Shape과 Appearance가 하나의 계수에 의해서 만들어 지는 Combined AAM이였고, 이후 Shape과 Appearance의 계수가 분리된 Independent AAM과 3D를 표현할 수 있는 Combined 2D+3D AAM이 개발 되었다. 비록 Combined 2D+3D AAM이 3D를 표현 할 수 있을지라도 이들은 공통적으로 2D 영상을 사용하여 모델을 생산한다. 본 논문에서 우리는 stereo-camera based 3D face capturing device를 통해 획득한 3D 데이터를 기반으로 하는 3D AAM을 제안한다. 우리의 3D AAM은 3D정보를 이용해 모델을 생산하므로 기존의 AAM보다 정확한 3D표현이 가능하고 Alignment Algorithm으로 Inverse Compositional Image Alignment(ICIA)를 사용하여 빠르게 Model Instance를 생산할 수 있다. 우리는 3D AAM을 평가하기 위해 stereo-camera based 3D face capturing device로 촬영해 수집한 한국인 얼굴 데이터베이스[9]로 얼굴인식을 수행하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.643-651
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• 2012

Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.137-144
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• 2014

This paper proposes a novel procedure that uses a combination of overlapped basic convex shapes to decompose 2D silhouette image. A basic convex shape is used here as a structuring element to give a meaningful interpretation to 2D images. Poisson equation is utilized to obtain the basic shapes for either the whole image or a partial region or segment of an image. The reconstruction procedure is used to combine the basic convex shapes to generate the original shape. The decomposition process involves a merging stage, filtering stage and finalized by compromising stage. The merging procedure is based on solving Poisson's equation for two regions satisfying the same symmetrical conditions which leads to finding equivalencies between basic shapes that need to be merged. We implemented and tested our novel algorithm using 2D silhouette images. The test results showed that the proposed algorithm lead to an efficient shape decomposition procedure that transforms any shape into a simpler basic convex shapes.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.21-28
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• 2011

A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• Architectural research
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• v.13 no.3
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• pp.19-29
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• 2011

Visibility of a space have been defined in several different ways: such as the axial line covering a convex space, a convex space defining the fattest shape in a space and an Isovist field formed by a field of vision at a given vantage point. Isovist fields are referred to as a descriptive medium to describe a movement by reviewing and analyzing geometric properties in them. Many descriptive methods for analysis of three-dimensional isovist are applied to analyzing the morphological properties in a 3D space more realistically. Although these models are regarded as a more advanced method for describing spatial properties, they have pros and cons such as complex mathematical calculations and somewhat arbitrary calibration in addition to huge consumption of memory space. These difficulties lead to the development of a three-dimensional visual accessibility model that explores the implication of building shape on the calculation of isovist fields drawn on a 2D plane. We propose a conceptual framework of how to measure the isovist field not as a 3D volume but as a combination of 2D plane on the ground with the 3D building shape of it's facade.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.122-131
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• 2011

A widely used single image-based 3D face reconstruction method, 3D morphable shape model, reconstructs an accurate 3D facial shape when 2D facial feature points are correctly extracted from an input face image. However, in the case that a user's cooperation is not available such as a real-time 3D face reconstruction system, this method can be vulnerable to the errors of automatic facial feature point extraction. In order to solve this problem, we automatically classify extracted facial feature points into two groups, erroneous and correct ones, and then reconstruct a 3D facial shape by using only the correctly extracted facial feature points. The experimental results showed that the 3D reconstruction performance of the proposed method was remarkably improved compared to that of the previous method which does not consider the errors of automatic facial feature point extraction.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.81-86
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• 2015

We fabricated a 3D knee joint model through the imaging processing. The 3D shape information is different depends on specific conditions when the shape of real knee joint is extracted from CT/MRI sliced images. The two types of joint models were fabricated by using 3D printer in order to analysis of joint movement by slight difference of 3D shape information. The compressive force experiments were performed by using knee joint model. As the results, the compressive forces were changed with respect to the difference of geometry. Consequently, feasibility test should be performed before developing biomimetic bioreactor.