• Title/Summary/Keyword: face modeling

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3D Face Modeling using Face Image

  • Kim, Sanghyuk;Ban, Yuseok;Park, Changhyun;Lee, Sangyoun
    • Journal of International Society for Simulation Surgery
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    • v.2 no.1
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    • pp.10-12
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    • 2015
  • Purpose It has been stated that patient satisfaction is the crucial factor for determining success in plastic surgery. The convergence of medical science and computer vision has made easier to satisfy patients who wants to have plastic surgery. In this paper, we try to apply 3D face modeling in plastic surgical area. Materials and Methods The author introduces a method for accurate 3D face modeling techniques using a statistical model-based 3D face modeling approach in a mirror system. Results We could successfully obtain highly accurate 3D face shape results. Conclusion The method suggested could be used for acquiring 3D face models from 2D face image and the result obtained from this could be effectively used for plastic surgical areas.

Personalized Face Modeling for Photorealistic Synthesis

  • Kim, Kyungmin;Shim, Hyunjung
    • Journal of International Society for Simulation Surgery
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    • v.2 no.2
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    • pp.47-51
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    • 2015
  • Faces play a key role in revealing the personalized attributes such as the identity, emotion, health condition, etc. Due to the importance of faces, computer-assisted face modeling and reconstruction have been actively studied both in computer vision and graphics community. Especially, face reconstruction and realistic face synthesis are well-grounded research problems and various approaches have been proposed during the last decade. In this paper, we discuss a wide range of existing work in face modeling by introducing their target applications, categorizing them upon their methodology and addressing their strength and weakness on performance. Finally, we introduce remaining research issues and suggest the future research direction in face modeling. We believe that this paper provides a high-level overview on face modeling techniques and helps understand the major research issues and the trends of methodology.

3D Face Modeling based on 3D Morphable Shape Model (3D 변형가능 형상 모델 기반 3D 얼굴 모델링)

  • Jang, Yong-Suk;Kim, Boo-Gyoun;Cho, Seong-Won;Chung, Sun-Tae
    • 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.

Non face-to-face News Articles Keyword Using Topic Modeling (토픽모델링을 이용한 비대면 신문 기사 키워드 분석)

  • Shin, Ari;Hwangbo, Jun Kwon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.11
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    • pp.1751-1754
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    • 2022
  • The news articles collected with keyword "non face-to-face" were analyzed through topic modeling applied with LDA algorithm. In this study, collected articles were divided into two periods, period 1(the beginning of COVID-19 spread) and period 2(the end of COVID-19 spread), according to issued date of the articles. The articles of period 1 showed support for non-face-to-face treatment, smart library, the beginning of the online financial era, non-face-to-face entrance exam and employment, stock investment for main topic words. And the articles of period 2 showed conversion to non face-to-face classes, increasing unmanned stores, online finance, education industry, home treatment for main topic words. Also, further issues were discussed through visualization of topic words. These results provide evidence that education and unmanned business in non-face-to-face industries are growing.

Pose-normalized 3D Face Modeling for Face Recognition

  • Yu, Sun-Jin;Lee, Sang-Youn
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.12C
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    • pp.984-994
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    • 2010
  • Pose variation is a critical problem in face recognition. Three-dimensional(3D) face recognition techniques have been proposed, as 3D data contains depth information that may allow problems of pose variation to be handled more effectively than with 2D face recognition methods. This paper proposes a pose-normalized 3D face modeling method that translates and rotates any pose angle to a frontal pose using a plane fitting method by Singular Value Decomposition(SVD). First, we reconstruct 3D face data with stereo vision method. Second, nose peak point is estimated by depth information and then the angle of pose is estimated by a facial plane fitting algorithm using four facial features. Next, using the estimated pose angle, the 3D face is translated and rotated to a frontal pose. To demonstrate the effectiveness of the proposed method, we designed 2D and 3D face recognition experiments. The experimental results show that the performance of the normalized 3D face recognition method is superior to that of an un-normalized 3D face recognition method for overcoming the problems of pose variation.

Pose-Normalized 3D Face Modeling (포즈 정규화된 3D 얼굴 모델링 기법)

  • Yu, Sun-Jin;Kim, Sang-Ki;Kim, Il-Do;Lee, Sang-Youn
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.455-456
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    • 2006
  • This paper presents an automatic pose-normalized 3D face data acquisition method using 2D and 3D information. We propose an automatic pose-normalized 3D face acquisition method that accomplishes 3D face modeling and 3D face pose-normalization at once. The proposed method uses 2D information with AAM (Active Appearance Model) and 3D information with 3D normal vector. The 3D face modeling system consists of 2 cameras and 1 projector. In order to verify proposed pose-normalized 3D modeling method, we made an experiment for 2.5D face recognition. The experimental result shows that proposed method is robust against pose variation.

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Ellipsoid Modeling Method for Coding of Face Depth Picture

  • Park, Dong-jin;Kwon, Soon-kak
    • Journal of Multimedia Information System
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    • v.6 no.4
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    • pp.245-250
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    • 2019
  • In this paper, we propose an ellipsoid modeling method for coding of a face depth picture. The ellipsoid modeling is firstly based on a point of a nose tip which is defined as the lowest value of the depth in the picture. The proposed ellipsoid representation is simplified through a difference of depth values between in the nose tip and in left or right boundary point of the face. Parameters of the ellipsoid are calculated through coordinates and depth values to minimize differences from the actual depth pixels. A picture is predicted by the modeled ellipsoid for coding of the face depth picture. In simulation results, an average MSEs between the face depth picture and the predicted picture is measured as 20.3.

Detection of Complaints of Non-Face-to-Face Work before and during COVID-19 by Using Topic Modeling and Sentiment Analysis (동적 토픽 모델링과 감성 분석을 이용한 COVID-19 구간별 비대면 근무 부정요인 검출에 관한 연구)

  • Lee, Sun Min;Chun, Se Jin;Park, Sang Un;Lee, Tae Wook;Kim, Woo Ju
    • The Journal of Information Systems
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    • v.30 no.4
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    • pp.277-301
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    • 2021
  • Purpose The purpose of this study is to analyze the sentiment responses of the general public to non-face-to-face work using text mining methodology. As the number of non-face-to-face complaints is increasing over time, it is difficult to review and analyze in traditional methods such as surveys, and there is a limit to reflect real-time issues. Approach This study has proposed a method of the research model, first by collecting and cleansing the data related to non-face-to-face work among tweets posted on Twitter. Second, topics and keywords are extracted from tweets using LDA(Latent Dirichlet Allocation), a topic modeling technique, and changes for each section are analyzed through DTM(Dynamic Topic Modeling). Third, the complaints of non-face-to-face work are analyzed through the classification of positive and negative polarity in the COVID-19 section. Findings As a result of analyzing 1.54 million tweets related to non-face-to-face work, the number of IDs using non-face-to-face work-related words increased 7.2 times and the number of tweets increased 4.8 times after COVID-19. The top frequently used words related to non-face-to-face work appeared in the order of remote jobs, cybersecurity, technical jobs, productivity, and software. The words that have increased after the COVID-19 were concerned about lockdown and dismissal, and business transformation and also mentioned as to secure business continuity and virtual workplace. New Normal was newly mentioned as a new standard. Negative opinions found to be increased in the early stages of COVID-19 from 34% to 43%, and then stabilized again to 36% through non-face-to-face work sentiment analysis. The complaints were, policies such as strengthening cybersecurity, activating communication to improve work productivity, and diversifying work spaces.

Light 3D Modeling with mobile equipment (모바일 카메라를 이용한 경량 3D 모델링)

  • Ju, Seunghwan;Seo, Heesuk;Han, Sunghyu
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.12 no.4
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    • pp.107-114
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    • 2016
  • Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.

Single Image-Based 3D Face Modeling for 3D Printing (3D 프린팅을 위한 단일 영상 기반 3D 얼굴 모델링 연구)

  • Song, Eungyeol;Koh, Wan-Ki;Yu, Sunjin
    • Journal of the Korean Society of Radiology
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    • v.10 no.8
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    • pp.571-576
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    • 2016
  • 3D printing has recently been used in various fields. Among various applications, 3D face data must be generated for 3D face printing. A laser scanner is used to acquire 3D face data, but there is a restriction that a person should not move during scanning. In this paper, we propose a 3D face modeling method based on a single image and a face transformation system to use the generated 3D face for virtual cosmetic surgery. We have defined facial feature points from the 3D face database for 3D face data generation. After extracting feature points from a single face image, 3D face of the input face image is generated corresponding to the 3D face feature points defined from the 3D face database. After 3D face modeling, 3D face modification part is applied for use such as virtual cosmetic surgery.