• 대한임베디드공학회논문지
• /
• 제9권5호
• /
• pp.261-268
• /
• 2014

Face detection is essential to the full automation of face image processing application system such as face recognition, facial expression recognition, age estimation and gender identification. It is found that local image features which includes Haar-like, LBP, and MCT and the Adaboost algorithm for classifier combination are very effective for real time face detection. In this paper, we present a face detection method using local pixel direction code(PDC) feature and lookup table classifiers. The proposed PDC feature is much more effective to dectect the faces than the existing local binary structural features such as MCT and LBP. We found that our method's classification rate as well as detection rate under equal false positive rate are higher than conventional one.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
• /
• pp.175-178
• /
• 2001

This paper proposes a novel human-computer interaction system for the disabled using recognition of face direction. Face direction is recognized by comparing positions of center of gravity between face region and facial features such as eyes and eyebrows. The face region is first selected by using color information, and then the facial features are extracted by applying a separation filter to the face region. The process speed for recognition of face direction is 6.57frame/sec with a success rate of 92.9% without any special hardware for image processing. We implement human-computer interaction system using screen menu, and show a validity of the proposed method from experimental results.

• 전자공학회논문지 IE
• /
• 제43권1호
• /
• pp.25-31
• /
• 2006

본 연구에서 기존 얼굴추출과 인식의 단점을 색상정보와 KLT를 이용하여 극복하고 얼굴 전체를 특징으로 하는 방법을 제안하였다. 얼굴의 특징은 KLT를 이용하는 PCA(Principal Component Analysis) 주성분 분석방법을 통해 중요한 정보만 추출하였다. 색상정보와 KLT를 이용한 얼굴인식의 방법을 제안함으로써 색상정보를 가진 다양한 크기와 각도의 얼굴에 대하여 90%이상의 인식 효율을 얻을 수 있었다.

• 산업기술연구
• /
• 제28권B호
• /
• pp.143-148
• /
• 2008

A real-time face detection is to find human faces robustly under the cluttered background free from the effect of occlusion by other objects or various lightening conditions. We propose a face detection system for real-time applications using wavelet decomposition method based on Gabor features. Firstly, skin candidate regions are extracted from the given image by skin color filtering and projection method. Then Gabor-feature based template matching is performed to choose face cadidate from the skin candidate regions. The chosen face candidate region is transformed into 2-level wavelet decomposition images, from which feature vectors are extracted for classification. Based on the extracted feature vectors, the face candidate region is finally classified into either face or nonface class by the Levenberg-Marguardt back-propagation neural network.

• Journal of Computing Science and Engineering
• /
• 제11권1호
• /
• pp.24-31
• /
• 2017

Face-based video retrieval has become an active and important branch of intelligent video analysis. Face profiling and matching is a fundamental step and is crucial to the effectiveness of video retrieval. Although many algorithms have been developed for processing static face images, their effectiveness in face-based video retrieval is still unknown, simply because videos have different resolutions, faces vary in scale, and different lighting conditions and angles are used. In this paper, we combined content-based and semantic-based image analysis techniques, and systematically evaluated four mainstream local features to represent face images in the video retrieval task: Harris operators, SIFT and SURF descriptors, and eigenfaces. Results of ten independent runs of 10-fold cross-validation on datasets consisting of TED (Technology Entertainment Design) talk videos showed the effectiveness of our approach, where the SIFT descriptors achieved an average F-score of 0.725 in video retrieval and thus were the most effective, while the SURF descriptors were computed in 0.3 seconds per image on average and were the most efficient in most cases.

• The International Journal of Costume Culture
• /
• 제6권2호
• /
• pp.93-104
• /
• 2003

The purpose of this study was to investigate the relationship between women's face satisfaction and makeup satisfaction, to disclose the differences of makeup satisfaction according to demographic variables, and to examine how makeup satisfaction was influenced by face satisfaction and demographic variables. The subjects were 200 women over age 17 living in Seoul and its peripheral areas. The results of this study were as follows: Face satisfaction were drawn three factors. Factor 1 was face contour satisfaction, Factor 2 was skin satisfaction, and Factor 3 was lips and eyes satisfaction. There were significant positive relationship between factors of face satisfaction and makeup satisfaction. Also, the face contour satisfaction was in positive correlation with satisfaction of features, and the skin satisfaction was in positive correlation with that of features. There were significant positive correlations between makeup satisfaction and face shape, eyes, nose, lips, chin, and cheek bone satisfaction. Face satisfaction didn't show significant difference according to demographic variables, but makeup satisfaction showed significant difference according to age and occupation. Face satisfaction was influenced by the facial face, clarity of skin, elasticity of skin, skin color, and ages. The explanatory power of the 4 variables were 24.5%. Makeup satisfaction was influenced by lips and eyes satisfaction, ages, and skin care level. The explanatory power of the 3 variables were 13.3%.

• Journal of information and communication convergence engineering
• /
• 제9권2호
• /
• pp.207-211
• /
• 2011

This paper presents a method for facial feature representation and recognition from the Covariance Matrices of the Gabor-filtered images. Gabor filters are a very powerful tool for processing images that respond to different local orientations and wave numbers around points of interest, especially on the local features on the face. This is a very unique attribute needed to extract special features around the facial components like eyebrows, eyes, mouth and nose. The Covariance matrices computed on Gabor filtered faces are adopted as the feature representation for face recognition. Geodesic distance measure is used as a matching measure and is preferred for its global consistency over other methods. Geodesic measure takes into consideration the position of the data points in addition to the geometric structure of given face images. The proposed method is invariant and robust under rotation, pose, or boundary distortion. Tests run on random images and also on publicly available JAFFE and FRAV3D face recognition databases provide impressively high percentage of recognition.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2007년도 하계종합학술대회 논문집
• /
• pp.385-386
• /
• 2007

In this paper, we present a detection method of facial angle using facial features. First, it finds face image using haar-like feature. After that, it finds eyes and lip in need of compute of face rotation angle. Next, it makes a triangle by using the facial features and computes the inside angle. As a result of experiment on various face images, the proposed method improves the efficiency much better than the conventional methods below $40^{\circ}$.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권6호
• /
• pp.817-828
• /
• 2004

본 논문에서는 몽타주 기법과 음영합성 기법을 이용한, 디자이너(예술가)의 감각을 살린 벡터 기반의 얼굴 생성 시스템을 제안한다. 제안하는 시스템은 사진으로부터 얼굴의 특징정보를 추출하여 사람의 얼굴과 유사한 얼굴을 자동으로 생성해 주는 시스템이며, 윤곽선만을 사용하던 기존의 얼굴 생성 시스템과 달리 컬러 기반이며, 음영을 사진으로부터 추출하여 이를 이목구비 이미지와 합성하여 생성하는 방식이다. 따라서 실사형에 좀 더 근접한 얼굴을 생성할 수 있다는 장점을 갖는다. 또, 벡터를 기반으로 하기 때문에 사이즈에 제한 얼이 자유로운 변형이 가능할 뿐만 아니라 디자이너 또는 그림 작가의 느낌을 결과물에 그대로 유지할 수 있도록 한다는 점에서 타 접근방식과의 차별성을 갖는다. 또, 2D 아바타에 자유로운 표정을 적용하는 데에도 쉽게 적용이 가능하다.

• 한국콘텐츠학회논문지
• /
• 제13권1호
• /
• pp.1-8
• /
• 2013

얼굴 영상 데이터베이스에서 제공하는 눈 좌표에 의존해서 부분 자동 얼굴 인식 알고리즘을 설계 구현하면 실 환경 얼굴 인식 시스템에서는 눈 좌표 추출 알고리즘의 정확도에 따라 인식 성능이 달라질 수 있다. 본 논문에서는 얼굴의 눈, 코, 입 및 윤곽선 정보를 바탕으로 설정한 특징점 기반의 얼굴 모델 그래프를 생성하여 얼굴 영상에 정합시키고 각 특징점에서 Gabor 및 LBP 피쳐를 추출해서 결합하는 방식의 완전 자동 얼굴 인식 알고리즘을 제안하였다. 본 알고리즘에서는 완전 자동으로 얼굴 영상에 얼굴 모델 그래프를 맞출 뿐만 아니라 기존의 Gabor 피쳐에 LBP 피쳐를 추가함으로써 인식 성능을 극대화 시킬 수 있도록 하였다. 제안한 알고리즘을 FERET 데이터베이스에 적용해 본 결과 1,000명 이상의 얼굴을 실시간으로 인식할 수 있었고 각 데이터 집합에 대해서 우수한 인식 성능을 얻을 수 있었다.