• Journal of the Institute of Electronics Engineers of Korea CI
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• 제47권3호
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• pp.11-21
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• 2010

To aim at improving performance and reflecting user's needs of retrieval, the number of researches has been actively conducted in recent year as the quantity of information and generation of the web pages exceedingly increase. One of alternative approaches can be a tagging system. It makes users be able to provide a representation of metadata including writings, pictures, and movies etc. called tag and be convenient in use of retrieval of internet resources. Tags similar to keywords play a critical role in maintaining target pages. However, they still needs time consuming labors to annotate tags, which sometimes are found to be a hinderance caused by overuse of tagging. In this paper, we present an automatic tagging scheme for a solution of current tagging system conveying drawbacks and inconveniences. To realize the approach, face recognition-based tagging system on SNS is proposed by building a face area detection procedure, linear-based classification and boosting algorithm. The proposed novel approach of tagging service can increase possibilities that utilized SNS more efficiently. Experimental results and performance analysis are shown as well.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제16권7호
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• pp.1495-1504
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• 2012

This paper proposes an algorithm to classify and analyze facial features such as eyebrow, eye, mouth and chin based on the geometric features of the face. As a preprocessing process to classify and analyze the facial features, the algorithm extracts the facial features such as eyebrow, eye, nose, mouth and chin. From the extracted facial features, it detects the shape and form information and the ratio of distance between the features and formulated them to evaluation functions to classify 12 eyebrows types, 3 eyes types, 9 mouth types and 4 chine types. Using these facial features, it analyzes a face. The face analysis algorithm contains the information about pixel distribution and gradient of each feature. In other words, the algorithm analyzes a face by comparing such information about the features.

• The KIPS Transactions:PartB
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• 제12B권7호
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• pp.795-802
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• 2005

In this paper, we present a facial expression recognition-synthesis system that recognizes 7 basic emotion information automatically and renders face with non-photorelistic style in PDA For the recognition of the facial expressions, first we need to detect the face area within the image acquired from the camera. Then, a normalization procedure is applied to it for geometrical and illumination corrections. To classify a facial expression, we have found that when Gabor wavelets is combined with enhanced Fisher model the best result comes out. In our case, the out put is the 7 emotional weighting. Such weighting information transmitted to the PDA via a mobile network, is used for non-photorealistic facial expression animation. To render a 3-D avatar which has unique facial character, we adopted the cartoon-like shading method. We found that facial expression animation using emotional curves is more effective in expressing the timing of an expression comparing to the linear interpolation method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제42권1호
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• pp.9-16
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• 2005

In this paper, we compare face recognition rate by distance change using Principal Component Analysis algorithm being input left and right image in stereo image. Change to YCbCr color space from RGB color space in proposed method and face region does detection. Also, after acquire distance using stereo image extracted face image's extension and reduce do extract robust face region, experimented recognition rate by using PCA algorithm. Could get face recognition rate of 98.61%(30cm), 98.91%(50cm), 99.05%(100cm), 99.90%(120cm), 97.31%(150cm) and 96.71%(200cm) by average recognition result of acquired face image. Therefore, method that is proposed through an experiment showed that can get high recognition rate if apply scale up or reduction according to distance.

• Proceedings of the KIEE Conference
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1997-1998
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• 2011

범용적으로 쓰여지고 있는 id카드를 이용한 출입방식의 경우 카드 분실, 미소지시 또는 손상시 불편함을 초래하며 실질적인 보안의 효과를 기대하기에는 부족한 부분이 많은 실정이다. 또한 전국에 사업장을 가지고 있는 기업의 경우는 보안업체별 소스코드를 공개하지 않음에 따라 id카드를 통일하기 위하여 최초 설치 업체에 종속되는 문제점도 가지고 있다. 그리고 지문인식, 홍체인식 및 정맥인식 등은 출입통제시스템 자체의 단점과 더불어 이용자들의 불편함 그리고 정보수집에 따른 불쾌감을 발생하는 문제점을 가지고 있다. 이러한 단점을 극복할수 있는 얼굴인식 시스템의 경우 다양한 상황에서의 얼굴 검출 및 정보 처리등에 대한 문제점이 있어 정지화상이나 신분증에 화상데이타를 입력하여 비교하는 방법등에 대한 실용화가 많이 되어지고 있는 실정이나 이 역시 id카드가 없으면 출입이 허가되지 않는다는 문제점이 있다. 이러한 문제점을 극복하고 자연스러운 상태에서 인증 및 출입이 허가된다면 가장 이상적이고 경제적인 출입통제시스템 구축이 가능하므로 본 논문에서는 위 문제점에 대한 대안을 제시하고 증명을 통하여 현장에서 충분이 적용될 수 있음을 입증하고자 한다.

• Journal of the Institute of Convergence Signal Processing
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• 제6권1호
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제22권5호
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• pp.251-256
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• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.

• Annual Conference of KIPS
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• 한국정보처리학회 2019년도 추계학술발표대회
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• pp.1110-1111
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• 2019

비전 기반 제스처 인식은 비 침입적이고 저렴한 비용으로 자연스러운 인간-컴퓨터 상호 작용을 제공한다. 로봇의 사용이 증가함에 따라 인간-로봇 상호 작용은 점점 더 중요해질 것이다. 최근 효율적인 딥러닝 기술이 연구되고 있다. 본 연구는 인간 컴퓨터 상호 작용을 위해 CNN을 기반으로 한 얼굴 및 손 동작의 인식을 위해 객체 검출 기법의 적용 결과를 제시한다.

• Proceedings of the KAIS Fall Conference
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• 한국산학기술학회 2010년도 춘계학술발표논문집 1부
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• pp.142-145
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• 2010

본 논문에서는 적외선 조명을 이용한 밝은 동공 효과와 전형적인 외형을 기반으로 한 사물 인식 기술을 결합하여 외부 조명의 간섭으로 밝은 동공 효과가 나타나지 않는 경우에도 견실하게 눈을 검출하고 추적 할 수 있는 방법을 제안한다. 눈 검출과 추적을 위해 SVM과 평균 이동 추적방법을 사용하였고, 적외선 조명과 카메라를 포함한 영상 획득 장치를 구성하여 제안된 방법이 효율적으로 다양한 조명하에서 눈 검출과 추적을 할 수 있음을 보여 주었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제30권7C호
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• pp.675-686
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• 2005

In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.