• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 한국방송∙미디어공학회 2022년도 하계학술대회
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• pp.1222-1225
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• 2022

본 논문에서는 저조도 환경에서 촬영된 영상의 조도를 개선하여 얼굴 검증 정확도를 높이는 방법을 제안하였다. 입력 이미지의 조도 개선을 통해 얼굴 검출 정확도를 개선하며, 검출된 얼굴의 반복적인 조도 향상을 통해 생성된 다수의 특징 벡터를 이용하여 얼굴 검증에 이용하였다. 얼굴 검출 및 검증 정확도 측정을 위해 K-FACE 데이터셋을 이용하였다. 저조도 환경에서 촬영된 검증 이미지에 대하여, 제안하는 특징 벡터 합성 방법으로 인해, 동일인 쌍 및 타인 쌍의 유사도 점수 분포의 표준 편차가 줄어드는 경향을 확인했으며, 이로 인해 검증 성능이 높아지는 결과를 얻었다.

• Journal of the Korean Institute of Intelligent Systems
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• 제15권2호
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• pp.163-172
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• 2005

When tracking a human face in the moving pictures with complex background under irregular lighting conditions, the detected face can be larger including background or smaller including only a part of the face. Even background can be detected as a face area. To solve these problems, this paper proposes a new face tracking method using a block difference image and a Kalman estimator. The block difference image allows us to detect even a small motion of a human and the face area is selected using the skin color inside the detected motion area. If the pixels with skin color inside the detected motion area, the boundary of the area is represented by a code sequence using the 8-neighbor window and the head area is detected analysing this code. The pixels in the head area is segmented by colors and the region most similar with the skin color is considered as a face area. The detected face area is represented by a rectangle including the area and its four vertices are used as the states of the Kalman estimator to trace the motion of the face area. It is proved by the experiments that the proposed method increases the accuracy of face detection and reduces the fare detection time significantly.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 한국방송공학회 2014년도 하계학술대회
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• pp.254-257
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• 2014

Recently, various applications using real-time face detection have been developed as face recognition technology and hardware grows. While network service is developing and video instruments costs lower, it is needed that smart surveillance camera and service using network camera based on IP and face detection technology. However, videos should be compressed for reducing network bandwidth and storage capacity in surveillance system. As it requires high-level improvement of system performance when all the compressed frames are processed in a face detection program, fast face detection method is needed. In this paper, not only a fast way of algorithm using Haar like features and adaboost learning and motion information but also an application on broadcast system is suggested.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제42권6호
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• pp.75-82
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• 2005

The robust feature vector selection method for the multiple frontal face detection is proposed in this paper. The proposed feature vector for the training and classification are integrated by means, amplitude projections, and its 1D Harr wavelet of the input image. And the statistical modeling is performed both for face and nonface classes. Finally, the estimated probability density functions (PDFs) are applied for the detection of multiple frontal faces in the still image. The proposed method can handle multiple faces, partially occluded faces, and slightly posed-angle faces. And also the proposed method is very effective for low quality face images. Experimental results show that detection rate of the propose method is $98.3\%$ with three false detections on the testing data, SET3 which have 227 faces in 80 images.

• Journal of Internet Computing and Services
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• 제3권6호
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• pp.13-24
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• 2002

This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.221-224
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• 2004

본 논문에서는 웹 카메라로 촬영된 받아진 입력영상에서 사람의 얼굴을 검출하고 검출된 얼굴을 기반으로 사람 얼굴 아바타를 생성하는 방법에 대하여 다루고 있다. 일반적으로 웹 카메라를 통해 얻은 영상은 해상도가 떨어질 뿐만 아니라 끊임없는 조명의 변화와 복잡한 배경이 존재하여 얼굴을 검출함에 있어 어려움을 준다. 따라서 몇몇의 특징 점에 의존하는 방법으로 사람얼굴의 윤곽선을 찾는다는 것은 큰 어려옴을 겪게 된다. 본 논문에서는 이런 방법들의 결점을 극복하기 위한 새로운 방법을 제안한다. 먼저 칼라정보를 이용하여 실험을 통하여 통계적으로 표준피부색을 정의하여 얼굴의 대략적인 위치와 크기를 얻은 다음으로 B-spline Snake를 이용하여 사람 얼굴의 윤곽선을 정확히 추출할 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(C)
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• pp.329-331
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• 2012

본 논문에서는 영상에서의 시각적 자극의 특징에 의한 돌출과 특정 대상에 관련한 단서들간의 상호작용에 기반하여 얼굴을 검출하는 주의집중모델을 제안한다. 제안하는 모델은 얼굴에 대한 하향식 다중 단서로 모양(shape), 피부색(skin color), 밝기(luminance), 거리에 대응하는 크기, 깊이 등을 사용하며 이들 단서들이 상향식 프로세스와의 상호작용을 통해 목표하는 얼굴을 검출하도록 유도하는 상향식/하향식 결합에 기반한다. 제안하는 방법은 크기 및 회전변화를 갖는 다수의 얼굴을 포함한 영상에서 얼굴검출을 수행함으로써 성능을 검증하였다.

• Journal of Korea Multimedia Society
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• 제9권1호
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• pp.11-22
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• 2006

Recently face detection has actively been researched due to its wide range of applications, such as personal identification and security systems. In this paper, a new face detection method based on the distribution map is proposed. Face-like regions are first extracted by applying the skin color map with the frequency to a color image and then, possible eye regions are determined by using the pupil color distribution map within the face-like regions. This enables the reduction of space for finding facial features. Eye candidates are detected by means of a template matching method using weighted window, which utilizes the correlation values of the luminance component and chrominance components as feature vectors. Finally, a cost function for mouth detection and location information between the facial features are applied to each pair of the eye candidates for face detection. Experimental results show that the proposed method can achieve a high performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제2권3호
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• pp.53-60
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• 2009

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking; and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2004년도 춘계종합학술대회
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• pp.603-607
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• 2004

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.