• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.735-739
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• 2005

This paper presents a new system to estimate the head pose of human in interactive indoor environment that has dynamic illumination change and large working space. The main idea of this system is to suggest a new morphological feature for estimating head angle from stereo disparity map. When a disparity map is obtained from stereo camera, the matching confidence value can be derived by measurements of correlation of the stereo images. Applying a threshold to the confidence value, we also obtain the specific morphology of the disparity map. Therefore, we can obtain the morphological shape of disparity map. Through the analysis of this morphological property, the head pose can be estimated. It is simple and fast algorithm in comparison with other algorithm which apply facial template, 2D, 3D models and optical flow method. Our system can automatically segment and estimate head pose in a wide range of head motion without manual initialization like other optical flow system. As the result of experiments, we obtained the reliable head orientation data under the real-time performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1471-1481
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• 1998

In this paper, we propose a new digital image stabilization scheme based on the bit-plane matching. In the proposed algorithm, the conventional motion estimation algorithms are applied to the binary images extracted from the bit-plane images. It is shown that the computational complexity of the proposed algorithm can be significantly reduced by replacing the arithmetic calculations with the binary Boolean functions, while the accuracy of motion estimation is maintained. Furthermore, an adaptive algorithm for selecting a bit-plane in consideration of changes in external illumination can provide the robustness of the proposed algorithm. We compared the proposed algorithm with existing algorithms using root mean square error (RMSE) on the basis of the brute-force method, and proved experimentally that the proposed method detects the camera motion more accurately than existing algorithms. In addition, the proposed algorithm performs digital image stabilization with less computation.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.697-699
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• 2005

본 논문에서는 실세계 조명 정보를 표현하는 HDR(High Dynamic Range) 영상으로부터 소수의 방향성 광원을 추정하는 기법을 제안한다. 광원 추정을 위해 노출 시간을 달리한 일련의 일반 영상으로부터 실세계의 조명 정보를 선형적으로 표현할 수 있는 HDR영상을 생성한다. HDR영상의 색상 및 명도 변화를 이용하며 영역을 분할하고, 분할된 영역으로부터 명도 평균과 가중치를 이용하여 방향성 광원의 파라미터를 추출하는 방법을 제안한다. 제안된 방법의 장정은 비반복적인 기법을 사용하여 일관된 결과를 산출하여 사용자의 입력없이 자동으로 계산하는 것이다. 추정된 광원은 그래픽 하드웨어를 사용한 실시간 렌더링에 적용 가능하다. 또한 실시간 렌더링이 중요한 가상현실이나 증강현실 분야에서 가상의 오브젝트를 렌더링할 때 IBL(Image Based Lighting)등의 전역조명 효과와 유사한 사실적인 영상을 얻을 수 있다.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1277-1282
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• 2006

본 논문에서는 배경과 오브젝트 합성 시 사실적인 그림자 효과를 표현하기 위해 HDR 영상을 기반으로 한 소수의 방향성 광원을 추정하는 기법을 제안한다. 실 세계 정보를 모두 포함하는HDR 영상을 가시화 하기 위해 톤 맵핑(tone mapping)하여 그 영상으로부터 광원의 위치가 되는 밝은 영역들을 찾아내고 그 위치들로부터 방향성 광원을 추정한다. 카메라의 노출시간을 짧게 하여 촬영한 영상에서 나타나는 부분을 실제 광원이 위치하는 부분으로 볼 수 있으므로 톤 맵핑한 영상을 이미지 프로세싱을 거쳐 노출 시간을 짧게 하여 촬영한 영상과 비슷한 결과를 얻을 수 있도록 한 후 밝은 영역만 표현 되도록 한다. 전 처리를 거친 영상을 기반으로 밝은 영역을 추정하기 때문에 보다 정확한 광원의 위치 추정이 가능하며, 추정된 밝은 영역과 일치하는 HDR 영상의 데이터를 사용하기 때문에 정확한 광원의 위치와 데이터를 얻을 수 있다. 또한 추정된 광원은 실제 렌더링에 곧바로 사용이 가능하며, 이를 통해 사실적인 shadowing 효과를 얻을 수 있다.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.149-154
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• 2014

Detection performance of fire detection in the outdoor depends on weather conditions, the shadow by the movement of the sun, or illumination changes. In this paper, a smoke detection in conjunction with a robust background estimate algorithm to environment change in the outdoor in daytime is proposed. Gaussian Mixture Model (GMM) is applied as background estimation, and also, statistical characteristics of smoke is applied to detect the smoke for separated candidate region. Through the experiments with input videos obtained from a various weather conditions, the proposed algorithms were useful to detect smoke in the outdoor.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.18-26
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• 2011

This paper presents a method, Exposure Controlled Temporal Filtering (ECF), applied to visual motion tracking, that can cancel the temporal aliasing of periodic vibrations of cameras and fluctuations in illumination through the control of exposure time. We first present a theoretical analysis of the exposure induced image time integration process and how it samples sensor impingent light that is periodically fluctuating. Based on this analysis we develop a simple method to cancel high frequency vibrations that are temporally aliased onto sampled image sequences and thus to subsequent motion tracking measurements. Simulations and experiments using the 'Center of Gravity' and Normalized Cross-Correlation motion tracking methods were performed on a microscopic motion tracking system to validate the analytical predictions.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1545-1546
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• 2008

In this study, an image processing method with FRANSAC(Fuzzy RANSAC) is presented and discussed for the development of a microscopic gap measuring algorithm. Many problems in edge detection processing are mainly occurred by the illumination system. A serious problem is that the edge set of gap could include the error elements that have relatively larger error than normal. This problem leads to a incorrect measurement of gap. We present a gap measuring algorithm using FRANSAC[1] that is a representative robust estimation algorithm. FRANSAC is peformed by first categorizing all data into good sample set, bad sample set and vague sample set using a fuzzy classification and then sampling in only good sample set. Experimental results show that the presented gap measuring algorithm gives a higher accurate value of gap especially for the more noisy image data.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.262-269
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• 2010

This paper presents a probabilistic head tracking method, mainly applicable to face recognition and human robot interaction, which can robustly track human head against various variations such as pose/scale change, illumination change, and background clutters. Compared to conventional particle filter based approaches, the proposed method can effectively track a human head by regularizing the sample space and sequentially weighting multiple visual cues, in the prediction and observation stages, respectively. Experimental results show the robustness of the proposed method, and it is worthy to be mentioned that some proposed probabilistic framework could be easily applied to other object tracking problems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1633-1641
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• 1996

In this paper we propose a new method for anlayzing the properties of surface reflectance and reconstructing the shape of object using estimated reflectance parameters. We have investigated the hybrid reflectance surface which has specularreflection and diffuse reflection, which can be explained by Torrance-Sparrow model. Sample sphere made on one maerial is used to estimate the reflectance properties by using LMS algorithm. We can make the reference image which consists of surface normal and brightness value using estimated reflectance parameters, and thenarbitrary shape object made of the same material as sample can be reconstructed by matching with reference image. Photometric matching method proposed in this paper is robust because it mateches object image with the reference imageconsidering its neighbor brightness distribution. Also, in this paper plate diffuse illumination is used to remove intensity disparity with simple scheme. It is expected that the proposed algorithm can be applied to 3D recognition, vision inspection system and other fields.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.65-70
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• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.