• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.333-334
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• 2016

본 논문은 광류와 템플릿 정합을 이용한 장기 객체 추적 기법을 제안한다. 템플릿 정합은 객체의 형태, 크기, 회전 등 변화에 취약하지만, 객체의 변화량이 적은 경우 검출 성능은 우수한 편이다. 동영상의 인접한 프레임들은 객체의 변화량이 크지 않아 템플릿 정합만으로도 검출이 가능하지만, 누적되는 오차로 인해 템플릿의 갱신이 필요하다. 하지만 템플릿 정합만으로는 갱신에 필요한 객체 영역을 특정할 수 없기 때문에, 광류를 이용하여 효과적으로 템플릿을 갱신할 수 있다. 이와 같은 구조의 적응형 템플릿 정합을 적용한 장기 객체 추적 기법을 제안하며, 모의 실험을 통해 장기 객체 추적이 가능함을 증명한다.

• The KIPS Transactions:PartA
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• v.17A no.4
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• pp.189-196
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• 2010

This paper presents an improved marker detection algorithm using hybrid features such as corner, line segment, region, and adaptive threshold values, etc. In usual augmented reality environments, there are often marker occlusion and poor illumination. However, existing ARToolkit fails to recognize the marker in these situations, especially, partial concealment of marker by user, large change of illumination and dim circumstances. In order to solve these problems, the adaptive threshold technique is adopted to extract a marker region and a corner extraction method based on line segments is presented against marker occlusions. In addition, a compensating method, corresponding the marker size and center between registered and extracted one, is proposed to increase the template matching efficiency, because the inside marker size of warped images is slightly distorted due to the movement of corner and warping. Therefore, experimental results showed that the proposed algorithm can robustly detect the marker in severe illumination change and occlusion environment and use similar markers because the matching efficiency was increased almost 30%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.99-108
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• 2004

In this paper, a new fast detection and clutter rejection method is proposed for CCD-image-based Automatic Target Detection System. For defence application, fast computation is a critical point, thus we concentrated on the ability to detect various targets with simple computation. In training stage, 1D template set is generated by regional vertical projection and K-means clustering, and binary tree structure is adopted to reduce the number of template matching in test stage. We also use adaptive skip-width by Correlation-based Adaptive Predictive Search(CAPS) to further improve the detecting speed. In clutter rejection stage, we obtain Fourier Descriptor coefficients from boundary information, which are useful to rejected clutters.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.722-730
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• 2012

Recently, eye image information has been widely used for iris recognition or gaze detection in biometrics or human computer interaction. According as long distance camera-based system is increasing for user's convenience, the noises such as eyebrow, forehead and skin areas which can degrade the accuracy of eye detection are included in the captured image. And fast processing speed is also required in this system in addition to the high accuracy of eye detection. So, we compared the most widely used algorithms for eye detection such as AdaBoost eye detection algorithm, adaptive template matching+AdaBoost algorithm, CAMShift+AdaBoost algorithm and rapid eye detection method. And these methods were compared with images including light changes, naive eye and the cases wearing contact lens or eyeglasses in terms of accuracy and processing speed.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1913_1914
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• 2009

본 논문에서 조명환경하에서 음성/영상 연동시스템을 통해서 외부음향잡음의 차단을 위한 강인한 입술움직임 영상영역을 추적하는 한 가지 방법을 제안한다. 조명환경하에서 강인한 입술움직임 영상영역을 추적하기 위해 온라인상에서 입술움직임 표준영상을 수집하였고 다양한 조명환경에 적응하는 입술 움직임 영상의 특징들을 추출하였다. 동시에 온라인 템플릿 영상을 획득하였고, 이 영상들을 템플릿 정합을 위해 사용했다. 음성/영상처리시스템의 연동결과, 다양한 조명환경하에서 그 연동률을 99.3%까지 높일 수 있었고 음향잡음에 의한 음성인식 실행을 원천적으로 차단할 수 있었다.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.45-56
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• 2015

In this paper we propose a very rapid moving object tracking method for an object-based auto focus on a smart phone camera. By considering the limit of non-learning approach on low-performance platforms, we use a sliding-window detection technique based on histogram features. By adapting the integral histogram, we solve the problem of the time-consuming histogram computation on each sub-window. For more speed up, we propose a local candidate search, and an adaptive scaling template method. In addition, we propose to apply a stabilization term in the matching function for a stable detection location. In experiments on our dataset, we demonstrated that we achieved a very rapid tracking performance demonstrating over 100 frames per second on a PC environment.