• Title/Summary/Keyword: Facial Model

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Facial Feature Tracking Using Adaptive Particle Filter and Active Appearance Model (Adaptive Particle Filter와 Active Appearance Model을 이용한 얼굴 특징 추적)

  • Cho, Durkhyun;Lee, Sanghoon;Suh, Il Hong
    • The Journal of Korea Robotics Society
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    • v.8 no.2
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    • pp.104-115
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    • 2013
  • For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.

Facial Feature Extraction using Multiple Active Appearance Model (Multiple Active Appearance Model을 이용한 얼굴 특징 추출 기법)

  • Park, Hyun-Jun;Kim, Kwang-Baek;Cha, Eui-Young
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.8
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    • pp.1201-1206
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    • 2013
  • Active Appearance Model(AAM) is one of the facial feature extraction techniques. In this paper, we propose the Multiple Active Appearance Model(MAAM). Proposed method uses two AAMs. Each AAM trains using different training parameters. It causes that each AAM has different strong points. One AAM complements the weak points in the other AAM. We performed the facial feature extraction on the 100 images to verify the performance of MAAM. Experiment results show that MAAM gives more accurate results than AAM with less fitting iteration.

SURGICAL INDEX FOR BONE SHAVING USING RAPID PROTOTYPING MODEL;TECHNICAL PROPOSAL FOR TREATMENT OF FIBROUS DYSPLASIA (Rapid Prototyping 모델을 이용한 골삭제을 위한 외과적 지표;섬유성 골이형성증 치료를 위한 기술적 제안)

  • Kim, Woon-Kyu
    • Maxillofacial Plastic and Reconstructive Surgery
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    • v.23 no.4
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    • pp.366-375
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    • 2001
  • Bone shaving for surgical correction is general method in facial asymmetrical patient with fibrous dysplasia. Therefore, decision of bone shaving amount on the preoperative planning is very difficult for improvement of ideal occlusal relationship and harmonious face. Preoperative planning of facial asymmetry with fibrous dysplasia is generally confirmed by the simulation surgery based on evaluation of clinical examination, radiographic analysis and analysis of facial study model. However, the accurate postoperative results can not be predicted by this method. By using the computed tomography based RP(rapid prototyping) model, simulation of facial skeleton can be duplicated and 3-dimensional simmulation surgery can be perfomed. After fabrication of postoperative study model by preoperactive bone shaving, preoperative and postoperactive surgical index was made by omnivaccum and clear acrylic resin. Amount of bone shaving is confirmed by superimposition of surgical index at the operation. We performed the surgical correction of facial asymmetry patients with fibrous dysplasia using surgical index and prototyping model and obtained the favorable results.

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Subdivided Facial Muscle Modeling based on MPEG-4 EAP (MPEG-4 FAP 기반 세분화된 얼굴 근육 모델 구현)

  • 이인서;박운기;전병우
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.631-634
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    • 2000
  • In this paper, we propose a method for implementing a system for decoding the parameter data based on Facial Animation Parameter (FAP) developed by MPEG-4 Synthetic/Natural Hybrid Coding (SNHC) subcommittee. The data is displayed according to FAP with human mucle model animation engine. Proposed model has the basic properties of the human skin specified by be energy funtional for realistic facial animation.

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Dynamic Emotion Model in 3D Affect Space for a Mascot-Type Facial Robot (3차원 정서 공간에서 마스코트 형 얼굴 로봇에 적용 가능한 동적 감정 모델)

  • Park, Jeong-Woo;Lee, Hui-Sung;Jo, Su-Hun;Chung, Myung-Jin
    • The Journal of Korea Robotics Society
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    • v.2 no.3
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    • pp.282-287
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    • 2007
  • Humanoid and android robots are emerging as a trend shifts from industrial robot to personal robot. So human-robot interaction will increase. Ultimate objective of humanoid and android would be a robot like a human. In this aspect, implementation of robot's facial expression is necessary in making a human-like robot. This paper proposes a dynamic emotion model for a mascot-type robot to display similar facial and more recognizable expressions.

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A Probabilistic Network for Facial Feature Verification

  • Choi, Kyoung-Ho;Yoo, Jae-Joon;Hwang, Tae-Hyun;Park, Jong-Hyun;Lee, Jong-Hoon
    • ETRI Journal
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    • v.25 no.2
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    • pp.140-143
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    • 2003
  • In this paper, we present a probabilistic approach to determining whether extracted facial features from a video sequence are appropriate for creating a 3D face model. In our approach, the distance between two feature points selected from the MPEG-4 facial object is defined as a random variable for each node of a probability network. To avoid generating an unnatural or non-realistic 3D face model, automatically extracted 2D facial features from a video sequence are fed into the proposed probabilistic network before a corresponding 3D face model is built. Simulation results show that the proposed probabilistic network can be used as a quality control agent to verify the correctness of extracted facial features.

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Feature Detection and Simplification of 3D Face Data with Facial Expressions

  • Kim, Yong-Guk;Kim, Hyeon-Joong;Choi, In-Ho;Kim, Jin-Seo;Choi, Soo-Mi
    • ETRI Journal
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    • v.34 no.5
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    • pp.791-794
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    • 2012
  • We propose an efficient framework to realistically render 3D faces with a reduced set of points. First, a robust active appearance model is presented to detect facial features in the projected faces under different illumination conditions. Then, an adaptive simplification of 3D faces is proposed to reduce the number of points, yet preserve the detected facial features. Finally, the point model is rendered directly, without such additional processing as parameterization of skin texture. This fully automatic framework is very effective in rendering massive facial data on mobile devices.

Development of a Ream-time Facial Expression Recognition Model using Transfer Learning with MobileNet and TensorFlow.js (MobileNet과 TensorFlow.js를 활용한 전이 학습 기반 실시간 얼굴 표정 인식 모델 개발)

  • Cha Jooho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.3
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    • pp.245-251
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    • 2023
  • Facial expression recognition plays a significant role in understanding human emotional states. With the advancement of AI and computer vision technologies, extensive research has been conducted in various fields, including improving customer service, medical diagnosis, and assessing learners' understanding in education. In this study, we develop a model that can infer emotions in real-time from a webcam using transfer learning with TensorFlow.js and MobileNet. While existing studies focus on achieving high accuracy using deep learning models, these models often require substantial resources due to their complex structure and computational demands. Consequently, there is a growing interest in developing lightweight deep learning models and transfer learning methods for restricted environments such as web browsers and edge devices. By employing MobileNet as the base model and performing transfer learning, our study develops a deep learning transfer model utilizing JavaScript-based TensorFlow.js, which can predict emotions in real-time using facial input from a webcam. This transfer model provides a foundation for implementing facial expression recognition in resource-constrained environments such as web and mobile applications, enabling its application in various industries.

Emotion Detection Algorithm Using Frontal Face Image

  • Kim, Moon-Hwan;Joo, Young-Hoon;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2373-2378
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    • 2005
  • An emotion detection algorithm using frontal facial image is presented in this paper. The algorithm is composed of three main stages: image processing stage and facial feature extraction stage, and emotion detection stage. In image processing stage, the face region and facial component is extracted by using fuzzy color filter, virtual face model, and histogram analysis method. The features for emotion detection are extracted from facial component in facial feature extraction stage. In emotion detection stage, the fuzzy classifier is adopted to recognize emotion from extracted features. It is shown by experiment results that the proposed algorithm can detect emotion well.

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Web-based 3D Face Modeling System (웹기반 3차원 얼굴 모델링 시스템)

  • 김응곤;송승헌
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.3
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    • pp.427-433
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    • 2001
  • This paper proposes a web-based 3 dimensional face modeling system that makes a realistic facial model efficiently without any 30 scanner or camera that uses in the traditional methods. Without expensive image-input equipments, we can easily create 3B models only using front and side images. The system is available to make 3D facial models as we connect to the facial modeling server on the WWW which is independent from specific platforms and softwares. This system will be implemented using Java 3D API, which includes the functions and conveniences of developed graphic libraries. It is a Client/server architecture which consists of user connection module and 3D facial model creating module. Clients connect with the facial modeling server, input two facial photographic images, detects the feature points, and then create a 3D facial model modifying generic facial model with the points according to the procedures using only the web browser.

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