• Title/Summary/Keyword: FACE

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Online Face Avatar Motion Control based on Face Tracking

  • Wei, Li;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.12 no.6
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    • pp.804-814
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    • 2009
  • In this paper, a novel system for avatar motion controlling by tracking face is presented. The system is composed of three main parts: firstly, LCS (Local Cluster Searching) method based face feature detection algorithm, secondly, HMM based feature points recognition algorithm, and finally, avatar controlling and animation generation algorithm. In LCS method, face region can be divided into many small piece regions in horizontal and vertical direction. Then the method will judge each cross point that if it is an object point, edge point or the background point. The HMM method will distinguish the mouth, eyes, nose etc. from these feature points. Based on the detected facial feature points, the 3D avatar is controlled by two ways: avatar orientation and animation, the avatar orientation controlling information can be acquired by analyzing facial geometric information; avatar animation can be generated from the face feature points smoothly. And finally for evaluating performance of the developed system, we implement the system on Window XP OS, the results show that the system can have an excellent performance.

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Invariant Range Image Multi-Pose Face Recognition Using Fuzzy c-Means

  • Phokharatkul, Pisit;Pansang, Seri
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1244-1248
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    • 2005
  • In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

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An Efficient Face Recognition using Feature Filter and Subspace Projection Method

  • Lee, Minkyu;Choi, Jaesung;Lee, Sangyoun
    • Journal of International Society for Simulation Surgery
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    • v.2 no.2
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    • pp.64-66
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    • 2015
  • Purpose : In this paper we proposed cascade feature filter and projection method for rapid human face recognition for the large-scale high-dimensional face database. Materials and Methods : The relevant features are selected from the large feature set using Fast Correlation-Based Filter method. After feature selection, project them into discriminant using Principal Component Analysis or Linear Discriminant Analysis. Their cascade method reduces the time-complexity without significant degradation of the performance. Results : In our experiments, the ORL database and the extended Yale face database b were used for evaluation. On the ORL database, the processing time was approximately 30-times faster than typical approach with recognition rate 94.22% and on the extended Yale face database b, the processing time was approximately 300-times faster than typical approach with recognition rate 98.74 %. Conclusion : The recognition rate and time-complexity of the proposed method is suitable for real-time face recognition system on the large-scale high-dimensional face database.

Measurement of Face Region Size in Motion Picture (동영상에서 블록화된 차영상 기반의 얼굴 영역 크기 측정 기법)

  • 장희준;고혜선;최영우;한헌수
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.313-316
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    • 2003
  • This paper proposes a new measurement method of face region size for real-time serveillance systems. The proposed method consists of three steps. In the first step, it detects global face area based on the block-based difference images. In the second step, it measures the face region size using face color information. In the third step, it estimates the face position in the next input image using the trajectory of face regions. The experimental results have shown that the proposed algorithm measures the face size within 20% relative error on average, which is a]towable for most surveillance systems.

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Improvement of Face Recognition Rate by Preprocessing Based on Elliptical Model (타원 모델기반의 전처리 기법에 의한 얼굴 인식률 개선)

  • Won, Chul-Ho
    • Journal of Korea Society of Industrial Information Systems
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    • v.13 no.4
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    • pp.56-63
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    • 2008
  • Image calibration at preprocessing step is very important for face recognition rate improvement, and background noise deletion affects accuracy of face recognition specially. In this paper, a method is proposed to remove background area utilizing elliptical model at preprocessing step for face recognition rate improvement. As human face has the shape of ellipse, a face contour can be easily detected by using the elliptical model in face images.

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Driver's Face Detection Using Space-time Restrained Adaboost Method

  • Liu, Tong;Xie, Jianbin;Yan, Wei;Li, Peiqin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.9
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    • pp.2341-2350
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    • 2012
  • Face detection is the first step of vision-based driver fatigue detection method. Traditional face detection methods have problems of high false-detection rates and long detection times. A space-time restrained Adaboost method is presented in this paper that resolves these problems. Firstly, the possible position of a driver's face in a video frame is measured relative to the previous frame. Secondly, a space-time restriction strategy is designed to restrain the detection window and scale of the Adaboost method to reduce time consumption and false-detection of face detection. Finally, a face knowledge restriction strategy is designed to confirm that the faces detected by this Adaboost method. Experiments compare the methods and confirm that a driver's face can be detected rapidly and precisely.

Detection of Face and Facial Features in Complex Background from Color Images (복잡한 배경의 칼라영상에서 Face and Facial Features 검출)

  • 김영구;노진우;고한석
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.69-72
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    • 2002
  • Human face detection has many applications such as face recognition, face or facial feature tracking, pose estimation, and expression recognition. We present a new method for automatically segmentation and face detection in color images. Skin color alone is usually not sufficient to detect face, so we combine the color segmentation and shape analysis. The algorithm consists of two stages. First, skin color regions are segmented based on the chrominance component of the input image. Then regions with elliptical shape are selected as face hypotheses. They are certificated to searching for the facial features in their interior, Experimental results demonstrate successful detection over a wide variety of facial variations in scale, rotation, pose, lighting conditions.

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Experimental Observation of Temporal Dark Image Sticking in AC PDP with Face-to-Face Sustain Electrode Structure

  • Kim, Jae-Hyun;Park, Choon-Sang;Kim, Bo-Sung;Park, Ki-Hyung;Tae, Heung-Sik
    • 한국정보디스플레이학회:학술대회논문집
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    • 2007.08a
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    • pp.617-620
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    • 2007
  • The temporal dark image sticking phenomena for both the face-to-face and coplanar sustain electrode structures were compared. For both structures, the temporal dark image sticking phenomena were examined by measuring the difference in the IR emission, display luminance, perceived luminance, and temperature between the image sticking and the no image sticking cells. For the face-to-face structure, the 10-min sustain discharge causes a small increment of the panel temperature thanks to the ITO-less electrode structure, thereby resulting in mitigating the temporal dark image sticking phenomenon.

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Physiological Neuro-Fuzzy Learning Algorithm for Face Recognition

  • Kim, Kwang-Baek;Woo, Young-Woon;Park, Hyun-Jung
    • Journal of information and communication convergence engineering
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    • v.5 no.1
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    • pp.50-53
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    • 2007
  • This paper presents face features detection and a new physiological neuro-fuzzy learning method by using two-dimensional variances based on variation of gray level and by learning for a statistical distribution of the detected face features. This paper reports a method to learn by not using partial face image but using global face image. Face detection process of this method is performed by describing differences of variance change between edge region and stationary region by gray-scale variation of global face having featured regions including nose, mouse, and couple of eyes. To process the learning stage, we use the input layer obtained by statistical distribution of the featured regions for performing the new physiological neuro-fuzzy algorithm.

Face-to-face Communication in Cyberspace using Analysis and Synthesis of Facial Expression

  • Shigeo Morishima
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1999.06a
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    • pp.111-118
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    • 1999
  • Recently computer can make cyberspace to walk through by an interactive virtual reality technique. An a avatar in cyberspace can bring us a virtual face-to-face communication environment. In this paper, an avatar is realized which has a real face in cyberspace and a multiuser communication system is constructed by voice transmitted through network. Voice from microphone is transmitted and analyzed, then mouth shape and facial expression of avatar are synchronously estimated and synthesized on real time. And also an entertainment application of a real-time voice driven synthetic face is introduced and this is an example of interactive movie. Finally, face motion capture system using physics based face model is introduced.