• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.17-22
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• 2003

In this paper, we propose the new side-view face detection method in color images which contain faces over one. It uses color and the geometrical distance between nose and chin. We convert RGB to YCbCr color space. We extract candidate regions of face using skin color information from image. And then, the extracted regions are processed by morphological filter, and the processed regions are labeled. Also, we correct the gradient of inclined face image using projected character of nose. And we detect the inclined side-view faces that have right and left 45 tips by within via ordinate. And we get 92% detection rate in 100 test images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.801-804
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• 2008

During face recognition process, face detection process is most preceding process. However, face has very high floating property, so the result could be very different according to which method we used. This paper studies about eye detection and eye blinking verification using edge and color information from YCbCr distribution map, segmentation, and labeling methods.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.67-74
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• 2001

In this paper, we propose a face detection algorithm using the color and shape information in color still images. The proposed algorithm is only applied to chrominance components(Cb and Cr) in order to reduce the variations of lighting condition in YCbCr color space. Input image is segmented by pixels with skin-tone color and then the segmented mage follows the morphological filtering an geometric correction to eliminate noise and simplify the segmented regions in facial candidate regions. Multiple facial regions in input images can be isolated by connected component labeling. Moreover tilting facial regions can be detected by extraction of second moment-based ellipse features.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.401-402
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• 2016

드론의 헬리캠, 스마트폰의 카메라를 통해 얼굴영상을 검출하고, 검출된 얼굴 영역을 지속적으로 추적하는 것은 최근 많은 연구가 진행 중에 있다. 특히 색상기반의 파티클 필터를 사용하는 얼굴추적기법은 빠르고 효과적이나 사용되는 파티클의 수와 윈도우즈의 크기 간의 상간관계는 연구된 바가 없다. 이 논문에서는 색상기반 파티클 필터를 이용하여 얼굴추적 시스템을 구축하고 파티클의 수와 윈도우즈의 크기간의 상관관계를 1집단부터 5집단에 대해 윈도우즈의 크기와 파티클의 수를 변화하며 인식률의 상관관계를 살펴보았다. 파티클의 수는 10부터 120개, 윈도우즈 크기는 20픽셀부터 200픽셀에 대해 실험한 결과 실험의 파티클의 수와 윈도우즈 크기는 인식률에 의미 있는 영향이 없음을 확인했다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.85-88
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• 2002

얼굴 영역을 검출하는 데 있어서 가장 기본적이면서도 중요한 정보가 컬러 정보이다. 하지만 컬러정보는 사용하는 컬러모델링 및 얼굴의 Skin Color를 평가하는 범위를 어떻게 정의하느냐에 따라 얼굴의 검출 성능에 많은 영향을 끼친다. 본 논문에서는 얼굴 영역을 검출하기 위한 첫 번째 조건으로 Skin color영역을 색상값과 다양한 데이터로부터 명암도에 따른 Skin color의 분포와 비율을 학습 함으로써 Skin color 영역을 검출 성능을 높이며, 퍼지 아트 알고리즘을 이용하여 얼굴과 비얼굴 데이터에 인증함으로써 얼굴 영역의 검출 성능을 높인다.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.197-204
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• 2008

It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.927-933
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• 2013

Face detection algorithm of OpenCV recognizes the faces by Haar matching between input image and Haar features which are learned through a set of training images consisting of many front faces. Therefore the face detection method by Haar matching yields a high face detection rate for the front faces but not in the case of the pan and deformed faces. On the assumption that distributional characteristics of color histogram is similar even if deformed or side faces, a face detection method using the histogram pattern matching is proposed in this paper. In the case of the missed detection and false detection caused by Haar matching, the proposed face detection algorithm applies the histogram pattern matching with the correct detected face area of the previous frame so that the face region with the most similar histogram distribution is determined. The experiment for evaluating the face detection performance reveals that the face detection rate was enhanced about 8% than the conventional method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.801-806
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• 2004

Although the technology for emotion recognition is important one which demanded in various fields, it still remains as the unsolved problem. Especially, it needs to develop the algorithm based on human facial image. In this paper, we propose the facial image analysis algorithm for emotion recognition. The proposed algorithm is composed as the facial image extraction algorithm and the facial component extraction algorithm. In order to have robust performance under various illumination conditions, the fuzzy color filter is proposed in facial image extraction algorithm. In facial component extraction algorithm, the virtual face model is used to give information for high accuracy analysis. Finally, the simulations are given in order to check and evaluate the performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1051-1054
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• 2011

사람의 신체 중 손, 발, 얼굴 부위는 오장육부와 관련이 있다. 이 중 발은 '제2의 심장'이라고까지 불러지고 있다. 이러한 내용은 발의 건강이 인체의 건강을 유지할 수 있고 혈액순환에도 중요하다는 의미도 있다. 본 논문에서는 발 지압점에서도 신장과 관련된 지압점이 있다는 내용을 기반으로 발 지압을 통한 얼굴의 색상 수치 변화를 분석하였다. 특히, 얼굴 부위 중 신장을 나타내는 지각 부위의 Lab 색체계에서 L값과 CMYK 색체계에서 K값의 변화를 분석하였다. 결론적으로 신장 발지압 자극에 따른 지각 부위의 색상 변화를 통한 지압의 효과성을 객관적으로 입증하는 실험을 수행하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.697-704
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• 2018

Since the face in image content corresponds to individual information that can distinguish a specific person from other people, it is important to accurately detect faces not hidden in an image. In this paper, we propose a method to accurately detect a face from input images using a deep learning algorithm, which is one of the machine learning methods. In the proposed method, image input via the red-green-blue (RGB) color model is first changed to the luminance-chroma: blue-chroma: red-chroma ($YC_bC_r$) color model; then, other regions are removed using the learned skin color model, and only the skin regions are segmented. A CNN model-based deep learning algorithm is then applied to robustly detect only the face region from the input image. Experimental results show that the proposed method more efficiently segments facial regions from input images. The proposed face area-detection method is expected to be useful in practical applications related to multimedia and shape recognition.