• 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.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.785-796
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• 2019

Due to the view point, illumination, personal gait and other background situation, person re-identification across cameras has been a challenging task in video surveillance area. In order to address the problem, a novel method called Joint Bayesian across different cameras for person re-identification (JBR) is proposed. Motivated by the superior measurement ability of Joint Bayesian, a set of Joint Bayesian matrices is obtained by learning with different camera pairs. With the global Joint Bayesian matrix, the proposed method combines the characteristics of multi-camera shooting and person re-identification. Then this method can improve the calculation precision of the similarity between two individuals by learning the transition between two cameras. For investigating the proposed method, it is implemented on two compare large-scale re-ID datasets, the Market-1501 and DukeMTMC-reID. The RANK-1 accuracy significantly increases about 3% and 4%, and the maximum a posterior (MAP) improves about 1% and 4%, respectively.

• 한국군사과학기술학회지
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• 제19권1호
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• pp.66-75
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• 2016

Stereoscopic image generated by depth image-based rendering(DIBR) for surveillance robot and camera is appropriate in a low bandwidth network. The image is very important data for the decision-making of a commander and thus its integrity has to be guaranteed. One of the methods used to detect manipulation is to check if the stereoscopic image is taken from the original camera. Sensor pattern noise(SPN) used widely for camera identification cannot be directly applied to a stereoscopic image due to the stereo warping in DIBR. To solve this problem, we find out a shifted object in the stereoscopic image and relocate the object to its orignal location in the center image. Then the similarity between SPNs extracted from the stereoscopic image and the original camera is measured only for the object area. Thus we can determine the source of the camera that was used.

• International Journal of Internet, Broadcasting and Communication
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• 제7권2호
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.

• International Journal of Internet, Broadcasting and Communication
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• 제10권1호
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• pp.16-22
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• 2018

This paper presents a solution for personal profiling system based on user-oriented tracking. Here, we introduce a new way to identify and track humans by using two types of cameras: dome and face camera. Dome camera has a wide view angle so that it is suitable for tracking human movement in large area. However, it is difficult to identify a person only by using dome camera because it only sees the target from above. Thus, face camera is employed to obtain facial information for identifying a person. In addition, we also propose a new mechanism to locate human on targeted location by using grid-cell system. These result in a system which has the capability of maintaining human identity and tracking human activity (movement) effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2075-2092
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• 2017

Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• International journal of advanced smart convergence
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• 제10권2호
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• pp.45-52
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• 2021

The surveillance camera market has developed and plays an important role in the field of video surveillance. However, in recent years, the identification of areas requiring surveillance has been limited by reflective light in the surveillance camera market. Cameras using polarization filters are being developed to reduce reflective light and facilitate identification. Programs are required to automatically adjust polarization filters. In this paper, we proposed an optimal angle extraction method from surveillance cameras using polarization filters through histogram analysis. First of all, transformed to grayscale to analyze the specifications of frames in multiple polarized angle images, reducing computational throughput. Then we generated and analyzed a histogram of the corresponding frame to extract the angle when the highlights are the fewest. Experiments with 0˚ and 90˚ showed high performance in extracting optimal angles. At this point, it is hoped this technology would be used for surveillance cameras in place like beach with a lot of reflective light.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 추계학술대회 논문집
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• pp.229-230
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• 2009

A method is suggested for the noise source identification using the sound intensity method. The suggested method does not need to install the grid using wire or thread during the sound intensity measurement for the noise source identification. It utilizes a camera to show the grid on the screen not installing the real grid for the sound intensity method.

• 한국정보기술학회논문지
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• 제17권8호
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• pp.11-19
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• 2019

영상 관련 범죄가 증가하고 고도화됨에 따라서 고수준의 디지털 포렌식 기술이 요구된다. 그러나 기존의 특징 기반 기술은 인간이 고안한 특징을 활용함으로서 새로운 기기 특징에 쉽게 대응하기 어렵고, 딥러닝 기반 기술은 정확도 향상이 요구된다. 본 논문에서는 딥러닝 모델 분야의 최신 기술인 DenseNet을 기반으로 카메라 모델 판별을 위한 딥러닝 모델을 제안한다. 카메라의 센서 특징을 획득하기 위해 HPF 특징 추출 필터를 적용하였고, 카메라 판별에 적합하도록 기존 DenseNet에서 계층 반복 수를 조정하였다. 또한 연산량을 줄이기 위한 Bottleneck layer와 압축 연산 처리를 제거하였다. 제안한 모델을 Dresden 데이터베이스를 사용하여 성능 분석을 하였고, 14개 카메라 모델에 대해 99.65%의 정확도를 달성하였다. 기존 연구들보다 높은 정확도를 달성하였으며 기존에 동일한 제조사에서 정확도가 낮아지는 단점을 극복하였다.