• 제목/요약/키워드: facial shape

검색결과 326건 처리시간 0.028초

모델기반 특징추출을 이용한 지역변화 특성에 따른 개체기반 표정인식 (Facial Expression Recognition with Instance-based Learning Based on Regional-Variation Characteristics Using Models-based Feature Extraction)

  • 박미애;고재필
    • 한국멀티미디어학회논문지
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    • 제9권11호
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    • pp.1465-1473
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    • 2006
  • 본 논문에서는 Active Shape Models(ASM)과 상태기반 모델을 사용하여 동영상으로부터 얼굴 표정을 인식하는 방법을 제시한다. ASM을 이용하여 하나의 입력 영상에 대한 얼굴요소특징점들을 정합하고, 그 과정에서 생성되는 모양변수벡터를 추출한다. 동영상에 대해 추출되는 모양변수벡터 집합을 세 가지 상태 중 한 가지를 가지는 상태벡터로 변환하고 분류기를 통해 얼굴의 표정을 인식한다. 분류단계에서는 표정별 표정변화에 따른 변화영역의 차이를 고려한 새로운 유사도 측정치를 제안한다. 공개데이터베이스 KCFD에 대한 실험에서는 제안한 측정치와 기존의 이친 측정치를 사용한 k-NN의 인식률이 k가 1일 때 각각 89.1% 및 86.2%을 보임으로써, 제안한 측정치가 기존의 이진 측정치보다 더 높은 인식률을 나타내는 것을 보인다.

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A Study on Personality Expression and the Awareness of Body Type - Focusing on Korea's Jeonnam Province and Yanbian, China College Students -

  • Jeong, Mi-Ae;Choi, Mee-Sung
    • 패션비즈니스
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    • 제13권3호
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    • pp.12-24
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    • 2009
  • This paper aims to investigate if a total of 266 college students from Yanbian, China, and Korea's Jeonnam Province are satisfied with their face and body type, and to find out an image-development method, depending on body characteristics. For this, a questionnaire survey using the 5-point Likert Scale was conducted, and an SPSS program has been used for data analysis. Besides the descriptive analysis, crosstab analysis, t-verification, and frequency analysis have been conducted. As body shape, posture, costume, accessories and makeup play an important role in image formation, this paper intends to form positive ego through exact awareness of the body shape by providing base data to a set image-development strategy. Then, the result has turned out as follows: First, in terms of the body index (i.e., Rohrer index), both Korea's Jeonnam Province and China's Yanbian college students were included in a category of the mean value. In terms of satisfaction with their body shape, on the contrary, China's China's Yanbian college students were higher than Korea's Jeonnam Province college students. Second, male China's Yanbian college students were slightly higher than female China's Yanbian college students in terms of satisfaction with their facial shape. However, the male students showed no big interest in facial care. Third, in terms of facial shape, an egg-shaped face was the most preferred in both China's Yanbian and Korea's Jeonnam Province college students, followed by an inverted triangle-shaped face in China's Yanbian college students and a diamond-shaped face in Korea's Jeonnam Province college students, showing significant difference ($p{\le}.001$). Even though both college students live in Northeast Asia, their preference on facial shape turned out to greatly differ, which indicates their different social environments. This paper will be helpful in global marketing for college students who are the major consumers in the future as Korean-Chinese exchange increases.

안정적인 실시간 얼굴 특징점 추적과 감정인식 응용 (Robust Real-time Tracking of Facial Features with Application to Emotion Recognition)

  • 안병태;김응희;손진훈;권인소
    • 로봇학회논문지
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    • 제8권4호
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    • pp.266-272
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    • 2013
  • Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

형상분류를 이용한 성인여성의 체질별 안면형태 특징에 관한 연구 (A Study on the Characteristics of Facial Shape in Adult Women by Sasang Constitution Using Hyungsang Classification)

  • 전수형;김종원
    • 사상체질의학회지
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    • 제29권2호
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    • pp.95-103
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    • 2017
  • Objectives This study was aimed to analyze characteristics of facial shapes in adult women by sasang constitution using hyungsang classification. Methods Using a digital camera, we took a picture of 1,011 women who participated in clinical study on menstrual pain and acquired their 3D facial images with a face-only scanner. They filled out SSCQ-P(sasang constitution questionnaire for patient) for the diagnosis of sasang constitution. Based on the above photographs and 3D images, one of the hyungsang medicine specialist diagnosed according to five diagnostic criteria. The sasang constitution was diagnosed by referring to questionnaires and photographs. Frequency analysis was performed using the statistical analysis system version 9.4 and chi-square test was performed for validity evaluation. Results In taeeumin, the wide face shape(n=261, 74.36%) was much more than the narrow shape(n=90, 25.64%) and the convex face profile(n=164, 85.86%) was much more than the concave profile(n=27, 14.14%). Regardless of sasang constitution, angular face shape(n=501, 50%) was the most, followed by oval shape(n=317, 31.64%). Subjects with big ears(n=291, 29.19%) were the most, while big eyes(n=104, 10.43%) were the least. Subjects with eyes and nose tip upward(n=615, 78.05%) were the most, while eyes and nose tip downward(n=22, 2.79%) were the least. Conclusions Most Korean adult women have angular face, such as square or diamond, with slanted eyes and upturned nose. Taeeumin women have wide facial shape and convex profile.

iOS 플랫폼에서 Active Shape Model 개선을 통한 얼굴 특징 검출 (Improvement of Active Shape Model for Detecting Face Features in iOS Platform)

  • 이용환;김흥준
    • 반도체디스플레이기술학회지
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    • 제15권2호
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    • pp.61-65
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    • 2016
  • Facial feature detection is a fundamental function in the field of computer vision such as security, bio-metrics, 3D modeling, and face recognition. There are many algorithms for the function, active shape model is one of the most popular local texture models. This paper addresses issues related to face detection, and implements an efficient extraction algorithm for extracting the facial feature points to use on iOS platform. In this paper, we extend the original ASM algorithm to improve its performance by four modifications. First, to detect a face and to initialize the shape model, we apply a face detection API provided from iOS CoreImage framework. Second, we construct a weighted local structure model for landmarks to utilize the edge points of the face contour. Third, we build a modified model definition and fitting more landmarks than the classical ASM. And last, we extend and build two-dimensional profile model for detecting faces within input images. The proposed algorithm is evaluated on experimental test set containing over 500 face images, and found to successfully extract facial feature points, clearly outperforming the original ASM.

Facial Expression Explorer for Realistic Character Animation

  • Ko, Hee-Dong;Park, Moon-Ho
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1998년도 Proceedings of International Workshop on Advanced Image Technology
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    • pp.16.1-164
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    • 1998
  • This paper describes Facial Expression Explorer to search for the components of a facial expression and to map the expression to other expressionless figures like a robot, frog, teapot, rabbit and others. In general, it is a time-consuming and laborious job to create a facial expression manually, especially when the facial expression must personify a well-known public figure or an actor. In order to extract a blending ratio from facial images automatically, the Facial Expression Explorer uses Networked Genetic Algorithm(NGA) which is a fast method for the convergence by GA. The blending ratio is often used to create facial expressions through shape blending methods by animators. With the Facial Expression Explorer a realistic facial expression can be modeled more efficiently.

Frontal augmentation as an adjunct to orthognathic or facial contouring surgery

  • Park, Young-Wook
    • Maxillofacial Plastic and Reconstructive Surgery
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    • 제38권
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    • pp.37.1-37.5
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    • 2016
  • Background: The dimensions and shape of the forehead determine the esthetics of the upper third of the face. Korean young people consider a broad and smooth, rounded forehead more attractive. As a result, frontal augmentation becomes more popular in patients with dentofacial deformities. Various surgical procedures and materials have been used in frontal augmentation surgery, with associated advantages and disadvantages. Silicone is a good candidate for frontal augmentation. The author presents two cases of esthetic frontal augmentation with a prefabricated silicone implant in female patients with dentofacial deformities. Case presentation: In case 1, a 24-year-old female patient underwent frontal augmentation surgery with simultaneous maxillomandibular and zygomatic osteotomies to correct facial asymmetry. A silicone implant was fabricated preoperatively using a positive template stone mold of her forehead. In case 2, a 23-year-old female patient underwent total facial contouring surgery including frontal augmentation for improved facial esthetics. A computed tomography (CT)-guided rapid prototype (RP) model was used to make the silicone implants. The operative procedure was safe and simple, and the silicone implants were reliable for a larger degree of frontal augmentation. Six months later, both patients had recovered from the surgery and were satisfied with their frontal shape and projection. Conclusions: Frontal augmentation with silicone implants can be an effective adjuvant strategy to improve facial esthetics in patients with a flat and narrow forehead who undergo orthognathic reconstruction or total facial contouring surgery.

컬러 정지 영상에서 색상과 모양 정보를 이용한 얼굴 영역 검출 (Facial Regions Detection Using the Color and Shape Information in Color Still Images)

  • 김영길;한재혁;안재형
    • 한국멀티미디어학회논문지
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    • 제4권1호
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    • pp.67-74
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    • 2001
  • 본 논문에서는 컬러 정지 영상에서 색상과 모양 정보를 이용한 얼굴 영역 검출 알고리즘을 제안한다. 제안된 알고리즘은 YCbCr 색공간에서 Cb와 Cr성분만을 이용하여 조명의 영향을 줄일 수 있다. 피부색 분할을 한후 얼굴 후보 영역들의 잡음 제거와 단순화를 위해 형태학적 필터와 기하학적 교정을 거친다. 입력 영상 내에 여러 사람이 존재할 경우에도 레이블링을 통해 각각의 얼굴 후보 영역들로 분리할 수 있고, 또한 2차 모멘트를 기반으로 한 타원 특징들을 추출하여 기울어진 얼굴 영역들도 성공적으로 검출할 수 있다.

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형태분석에 의한 특징 추출과 BP알고리즘을 이용한 정면 얼굴 인식 (Full face recognition using the feature extracted gy shape analyzing and the back-propagation algorithm)

  • 최동선;이주신
    • 전자공학회논문지B
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    • 제33B권10호
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    • pp.63-71
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    • 1996
  • This paper proposes a method which analyzes facial shape and extracts positions of eyes regardless of the tilt and the size of input iamge. With the extracted feature parameters of facial element by the method, full human faces are recognized by a neural network which BP algorithm is applied on. Input image is changed into binary codes, and then labelled. Area, circumference, and circular degree of the labelled binary image are obtained by using chain code and defined as feature parameters of face image. We first extract two eyes from the similarity and distance of feature parameter of each facial element, and then input face image is corrected by standardizing on two extracted eyes. After a mask is genrated line historgram is applied to finding the feature points of facial elements. Distances and angles between the feature points are used as parameters to recognize full face. To show the validity learning algorithm. We confirmed that the proposed algorithm shows 100% recognition rate on both learned and non-learned data for 20 persons.

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Reconstructing 3-D Facial Shape Based on SR Imagine

  • Hong, Yu-Jin;Kim, Jaewon;Kim, Ig-Jae
    • Journal of International Society for Simulation Surgery
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    • 제1권2호
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    • pp.57-61
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    • 2014
  • We present a robust 3D facial reconstruction method using a single image generated by face-specific super resolution technique. Based on the several consecutive frames with low resolution, we generate a single high resolution image and a three dimensional facial model based on it. To do this, we apply PME method to compute patch similarities for SR after two-phase warping according to facial attributes. Based on the SRI, we extract facial features automatically and reconstruct 3D facial model with basis which selected adaptively according to facial statistical data less than a few seconds. Thereby, we can provide the facial image of various points of view which cannot be given by a single point of view of a camera.