• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.1-8
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• 2007

The images, which were acquired from various systems such as CCTV and Robot, include many human faces. Because of a rapid increase in visual data, we cannot process these manually; rather we need to do these automatically. Furthermore, companies require automatic security systems to protect their new technology. There are various options available to us, including face recognition, iris recognition and fingerprint recognition. Face recognition is preferable since it does not require direct contact. However, the standard 2-Dimensional method is limited, so Morphable Models may be recommended as an alternative. The original morphable model, made by MPI, contains a large quantity of data such as texture and geometry data. This paper presents a Geometrix-based morphable model designed to reduce this data capacity.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.111-114
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• 2006

This paper presents Morphable Model Construction which is based GeometriX tool processing various data array such as texture space and geometry(shape space) in order to reduce calculation cost due to rapid advancement of face recognition speed. It introduces efficiently vertex and pixel reduction for raw data, which is based GeometriX tool using stereo scan.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.606-611
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• 2009

This paper describes a method for achieving a novel design within a class of 3D objects that would create a preferred impression on users. Physical parameters of the 3D objects that might strongly contribute to their visual impressions are sought through computational investigation of the impression ratings obtained for learning samples. "Car body" was selected as the class of 3D objects to be investigated. A morphable 3D model of car bodies that describes the variations in appearance using a smaller number of parameters was obtained. Based on each car body's rating for the impression of speediness obtained by paired comparison, the visual impression was transformed by manipulating the parameters defined in the morphable 3D model. The validity of the proposed method was confirmed by psychological experiments. A new scheme is also proposed to properly re-sample a novel object of a peculiar shape so that such an object could also be represented by the morphable 3D model.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.723-727
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• 2008

2D face analysis has some limitations which are pose and illumination sensitive. For these reasons, even if many researchers try to study in the 3D face analysis and processing, because of the low computing performance and the absence of a high-speed 3D scanner then a lot of research is not being able to proceed. But, due to improving of the computing performance in these days, the advanced 3D face research was now underway. In this paper, we propose the method of building a 3D face model which deal successfully with dense correspondence problem.

• Journal of KIISE:Software and Applications
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• v.34 no.5
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• pp.476-486
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• 2007

This paper proposes a resolution enhancement method which can reconstruct high-resolution facial images from single-frame, low-resolution facial images. The proposed method is derived from example-based reconstruction methods and the morphable face model. In order to improve the performance of the example-based reconstruction, we propose the region-based reconstruction method which can maintain the characteristics of local facial regions. Also, in order to use the capability of the morphable face model to face resolution enhancement problems, we define the extended morphable face model in which an extended face is composed of a low-resolution face, its interpolated high-resolution face, and the high-resolution equivalent, and then an extended face is separated by an extended shape vector and an extended texture vector. The encouraging results show that the proposed methods can be used to improve the performance of face recognition systems, particularly to enhance the resolution of facial images captured from visual surveillance systems.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.212-227
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• 2008

Since 3D face can be rotated freely in 3D space and illumination effects can be modeled properly, 3D face modeling Is more precise and realistic in face pose, illumination, and expression than 2D face modeling. Thus, 3D modeling is necessitated much in face recognition, game, avatar, and etc. In this paper, we propose a 3D face modeling method based on 3D morphable shape modeling. The proposed 3D modeling method first constructs a 3D morphable shape model out of 3D face scan data obtained using a 3D scanner Next, the proposed method extracts and matches feature points of the face from 2D image sequence containing a face to be modeled, and then estimates 3D vertex coordinates of the feature points using a factorization based SfM technique. Then, the proposed method obtains a 3D shape model of the face to be modeled by fitting the 3D vertices to the constructed 3D morphable shape model. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method builds a 3D face model by rendering the 3D face shape model with the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise than the previous 3D face model methods.

• 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 Broadcast Engineering
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• v.23 no.5
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• pp.614-621
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• 2018

This paper proposes a method of restoring corrupted depth image captured by depth camera through unsupervised learning using generative adversarial network (GAN). The proposed method generates restored face depth images using 3D morphable model convolutional neural network (3DMM CNN) with large-scale CelebFaces Attribute (CelebA) and FaceWarehouse dataset for training deep convolutional generative adversarial network (DCGAN). The generator and discriminator equip with Wasserstein distance for loss function by utilizing minimax game. Then the DCGAN restore the loss of captured facial depth images by performing another learning procedure using trained generator and new loss function.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.264-272
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• 2019

In this paper, we propose a 3D human body reconstruction and refinement method from the frames extracted from a video to obtain natural and smooth motion in temporal domain. Individual frames extracted from the video are fed into convolutional neural network to estimate the location of the joint and the silhouette of the human body. This is done by projecting the parameter-based 3D deformable model to 2D image and by estimating the value of the optimal parameters. If the reconstruction process for each frame is performed independently, temporal consistency of human pose and shape cannot be guaranteed, yielding an inaccurate result. To alleviate this problem, the proposed method analyzes and interpolates the principal component parameters of the 3D morphable model reconstructed from each individual frame. Experimental result shows that the erroneous frames are corrected and refined by utilizing the relation between the previous and the next frames to obtain the improved 3D human reconstruction result.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.213-214
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• 2007