• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.655-664
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• 2019

In this paper, we propose a novel way of combining multiple deep convolutional neural network (DCNN) architectures which work well for accurate video face identification by adopting a serial combination of 3D and 2D DCNNs. The proposed method first divides an input video sequence (to be recognized) into a number of sub-video sequences. The resulting sub-video sequences are used as input to the 3D DCNN so as to obtain the class-confidence scores for a given input video sequence by considering both temporal and spatial face feature characteristics of input video sequence. The class-confidence scores obtained from corresponding sub-video sequences is combined by forming our proposed class-confidence matrix. The resulting class-confidence matrix is then used as an input for learning 2D DCNN learning which is serially linked to 3D DCNN. Finally, fine-tuned, serially combined DCNN framework is applied for recognizing the identity present in a given test video sequence. To verify the effectiveness of our proposed method, extensive and comparative experiments have been conducted to evaluate our method on COX face databases with their standard face identification protocols. Experimental results showed that our method can achieve better or comparable identification rate compared to other state-of-the-art video FR methods.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제12권3호
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• pp.171-190
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• 2008

With growing applications of wireless video streaming, an efficient video traffic model featuring modern high-compression techniques is more desirable than ever, because the wireless channel bandwidths are ever limited and time-varying. We propose a modeling and analysis method for video traffic by a class of stochastic processes, which we call '$GEO^Y/G/{\infty}$ input processes'. We model video traffic by $GEO^Y/G/{\infty}$ input process with gamma-distributed batch sizes Y and Weibull-like autocorrelation function. Using four real-encoded, full-length video traces including action movies, a drama, and an animation, we evaluate our modeling performance against existing model, transformed-M/G/${\infty}$ input process, which is one of most recently proposed video modeling methods in the literature. Our proposed $GEO^Y/G/{\infty}$ model is observed to consistently provide conservative performance predictions, in terms of packet loss ratio, within acceptable error at various traffic loads of interest in practical multimedia streaming systems, while the existing transformed-M/G/${\infty}$ fails. For real-time implementation of our model, we analyze G/D/1/K queueing systems with $GEO^Y/G/{\infty}$ input process to upper estimate the packet loss probabilities.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.218-221
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• 2000

In this paper, we propose a new algorithm to detect human faces for controling a camera used in video conference. We model the distribution of skin color and set up the standard skin color in YIQ color space. An input video frame image is segmented into skin and non-skin segments by comparing the standard skin color and each pixels in the input video frame. Then, shape filler is applied to select face segments from skin segments. Our algorithm detects human faces in real time to control a camera to capture a human face with a proper size and position.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1996년도 학술대회
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• pp.153-158
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• 1996

Delay and jitter are critical factors in the real-time video services over ATM network. Mostly, delay and jitter problem are generated in input buffer when video are multiplexed. In this paper, we analyze delay and jitter of input buffer, and consider efficient control and flexible bandwidth allocation of video traffic. Also, we analyze decision of buffer size related maximum allowable delay.

• Journal of Information Technology Applications and Management
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• 제13권3호
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• pp.75-87
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• 2006

In this paper. we consider the multi-view video technology. The technology, which is a field of 3-Dimensional video processing, enables the user to watch the various view-point of video. We expect that the technology will be applicable to a lot of video services. The economic effects of new technology are very important concern for the technology developer and the technology development policy makers. We, therefore. propose a general method for the economic repercussion effects of the multi-view video technology. The method is based on the expert opinion and input-output analysis. The results for the multi-view video technology are included.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권3호
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• pp.1040-1057
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• 2014

In this paper, a new bit rate estimation scheme is proposed to determine the bit rate for each subclass in an MPEG-2 TS to H.264/AVC transcoder after dividing an input MPEG-2 TS sequence into several subclasses. Video format transcoding in conventional IPTV and Smart TV services is a time-consuming process since the input sequence should be fully transcoded several times with different bit-rates to decide the bit-rate suitable for a service. The proposed scheme can automatically decide the bit-rate for the transcoded video sequence in those services which can be stored on a video streaming server as small as possible without losing any subject quality loss. In the proposed scheme, an input sequence to the transcoder is sub-classified by hierarchical clustering using a parameter value extracted from each frame. The candidate frames of each subclass are used to estimate the bit rate using a statistical analysis and a mathematical model. Experimental results show that the proposed scheme reduces the bit rate by, on an average approximately 52% in low-complexity video and 6% in high-complexity video with negligible degradation in subjective quality.

• 한국정보시스템학회지:정보시스템연구
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• 제32권2호
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• pp.87-108
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• 2023

Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.

• 한국산업정보학회논문지
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• 제8권2호
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• pp.38-44
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• 2003

본 논문에서는 화상회의 시스템의 구조 및 입출력 모델의 분석을 통하여 시스템 버스의 병목현상을 개선하기 위해서 멀티미디어 데이터가 네트워크 접속장치로부터 주 기억 장치 및 멀티미디어 처리장치에 동시에 전송될 수 있는 방법을 제안한다. 제안한 방법은 화상회의 시스템에서 시스템 버스의 사용횟수, 버스 사이클, 데이터의 전송시간 및 비디오 데이터의 압축비를 줄일 수 있다. 본 논문에서 제안한 방법을 다자간 화상회의 시스템에 적용하여 기존의 방법과 성능을 비교하였다. 시뮬레이션 결과, 제안한 방법이 기존의 방법보다 멀티미디어 데이터의 전송 시간을 감소시킬 수 있음을 확인하였다.

• 한국인터넷방송통신학회논문지
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• 제14권1호
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• pp.169-177
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• 2014

DVR 및 NVR을 이용한 디지털 저장매체를 영상감시 시스템에서 활용하게 되면서 영상처리 모듈의 개발은 영상 보안 시장의 필수적인 요소이다. 특히 네트워크 카메라의 등장은 기존 아날로그 방식의 CCTV를 대체하면서 영상처리 모듈 개발의 필요성을 더욱 부각시키고 있다. 본 논문에서는 움직임 감지 기법을 이용한 영상 감시 서버를 설계 및 구축하고 서버에서 처리되는 영상처리 결과를 실시간으로 모바일 디바이스에서 확인 가능한 영상감시 시스템을 개발하였다. 영상처리를 위해 리눅스 기반의 서버에 오픈소스 OpenCV를 활용한 영상처리 모듈을 개발하였고, 네트워크 카메라로부터 전송되는 실시간 비디오 데이터를 저장 및 가공하여 안드로이드기반 모바일 기기에서 검색 가능한 영상감시 시스템을 구축하였다.

• 한국빅데이터학회지
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• 제7권1호
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• pp.99-111
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• 2022

불확실성과 복잡성이 존재하는 제조시스템의 생산성 분석과 의사결정을 위하여 시뮬레이션 기법이 활용될 수 있다. 이러한 시스템의 시뮬레이션을 위해 대상의 특성을 반영하는 입력 모델링 과정이 필요하다. 하지만 건설기계 조립라인과 같은 수작업 중심과 긴 리드타임을 가지는 복잡한 환경에서는 시뮬레이션에 활용할 데이터의 수집이 제한된다. 본 연구는 입력 데이터의 수집이 어려운 환경에서 동영상 데이터를 이용한 시뮬레이션 입력 모델링 절차를 제안한다. 동영상 데이터 기반 작업분석을 통해 측정시간을 정미시간과 표준시간으로 산정하고, 시뮬레이션의 입력 분포로 활용할 수 있다. 제안하는 절차로 산정된 확률분포를 시뮬레이션에 이용하여 대상 시스템의 주요 생산성 지표를 분석하였다. 본 연구에서 제안하는 절차는 데이터가 적은 상황에서 시뮬레이션을 활용한 생산성 분석으로 의사결정 보조에 도움을 줄 것으로 기대된다.