• 한국정보기술학회논문지
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• 제17권8호
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• pp.1-9
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• 2019

현대 사회에서 영상 정보 통신 기술이 발전함에 따라서 영상 획득 및 대량 생산 기술도 급속히 발전하였지만 이를 이용한 범죄도 증가하여 범죄 예방을 위한 법의학 연구가 진행되고 있다. 영상 획득 장치에 대한 판별 기술은 많이 연구되었지만, 그 분야가 영상으로 한정되어 있다. 본 논문에서는 영상이 아닌 동영상에 대한 카메라 모델의 판별 기법을 제안한다. 기존의 영상을 학습한 모델을 사용하여 동영상의 프레임을 분석하였고, 동영상의 프레임 특성을 활용한 학습과 분석을 통하여 P 프레임을 활용한 모델의 우수성을 보였다. 이를 이용하여 다수결 기반 판별 알고리즘을 적용한 동영상에 대한 카메라 모델 판별 시스템을 제안하였다. 실험에서는 5개 비디오 카메라 모델을 이용하여 분석을 하였고, 각각의 프레임 판별에 대해 최대 96.18% 정확도를 얻었으며, 비디오 카메라 모델 판별 시스템은 각 카메라 모델에 대하여 100% 판별률을 달성하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Bulletin of the Korean Chemical Society
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• 제16권7호
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• pp.661-666
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• 1995

The surface structure of the adsorption site for the identification of active sites involved in the Ziegler-Natta catalyst was studied by surface science techniques. As an example of a real catalyst, TiCl3 single crystals were prepared in a gradient furnace designed for this study and characterized by Auger Electron Spectroscopy (AES) and Low Energy Electron Diffraction (LEED) under ultrahigh vacuum condition. The chlorine covered Ti (0001) surface was employed as a model catalyst for the study of Ziegler-Natta catalyst. The diffuse LEED (DLEED) technique for the surface structural determination was applied to this disordered chlorine adsorbed on Ti (0001) surface. The diffuse scattering intensities were measured by a TV-computer method using a low light level video camera. From an analysis of two catalyst systems, the informations for the surface structure of the model catalyst surfaces were derived.