• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.139-142
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• 2013

최근 대용량 영상데이터로부터 정보 수집, 영상 처리를 위한 클라우드 관련 연구들이 활발하다. 그러나 공개 소프트웨어를 이용한 클라우드 연구의 대부분은 라이브러리 수준이 아닌 단순히 프로그램 수준의 조합으로 작동한다. 이런 이유로 단순 조합에 따른 비효율성에 의한 성능문제는 크게 다루어지지 않는다. 본 논문에서는 이 비효율성을 해결하는데 중점을 두고 FFmpeg과 Hadoop을 라이브러리 수준으로 결합하여 기존보다 더 나은 성능의 영상클라우드 환경을 구축하였다. C기반의 영상처리 라이브러리인 FFmpeg와 JAVA기반의 클라우드 환경 Hadoop의 결합을 위해 JNI(Java Native Interface)를 이용하였다. 상세구현으로는 HDFS(Hadoop Distributed File System)을 확장하여 Hadoop MapReduce가 직접 FFmpeg을 통한 영상파일 접근이 가능하게 하였다. 이로써 FFmpeg과 Hadoop간 상이한 파일 접근 방식에서 발생하는 불필요한 작업에 의한 시스템의 성능저하를 막았다. 또한 응용의 확장성을 위해 영상작업시 작업영상을 영상처리의 최소단위인 GOP(Group of Pictures)단위로 잘라 클라우드의 노드들에게 분산시켰다. 결과적으로 기존에 존재하는 Hadoop과 FFmpeg을 프로그램적으로 결합한 영상처리 클라우드보다 총 처리시간을 앞당겼고, GOP 단위의 영상 처리는 영상기반 작업에 안정성과 응용의 확장성을 보장해주었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.366-369
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• 2021

본 논문에서는 동영상에서 일련의 과정을 거쳐 얻었던 학습데이터를 보다 간편하고 빠른 속도로 획득하는 방법을 제안한다. 음성과 영상 스트림을 처리하는 ffmpeg을 이용해 영상을 프레임화하고, 딥 러닝 기반의 YOLO 알고리즘을 사용하여 객체를 검출한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.977-982
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• 2014

In this paper, we propose a system which can detect the flame in real time from the high-quality IP camera. First, open directly the RTSP streams transmitted from the IP camera using the library FFmpeg as opening a video file. The second thing is to extract the background images from video signal using Gaussian mixture model. Then the foreground images are obtained through subtracting operation between the input image and the background image. Separated foreground image through a mathematical morphology operation are considered as candidate area. By analysing colour information and dynamic characteristics of the candidate area, flame is determined finally. Through the experiments with input videos from IP camera, the proposed algorithms were useful to detect flames.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.3
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• pp.206-211
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• 2014

In this Paper, We proposed the HLS(Http Live Streaming) transmitter which is operated easily and cheap in all networks and client environments compared to the exist video live streaming transmitter. We analyzed the HLS protocol and then implemented for making the HLS transmitter cheaper and portable. After designing the HLS transmitter hardware using the RISC processor of Arm11 core, we ported the Linux Operating System and implemented the HLS protocol using the open source FFmpeg and Segmenter. For the performance evaluation of the developed HLS transmitter, we made the testing environment which is including the notebook, iPhone, and aroid Phone. In this testing environment, we analysed the received video data at the client displayer. As a results of the performance evaluation, we could certify that the proposed HLS transmitter has a higher performance than the Apple company's HLS.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.141-148
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• 2015

In this paper, for developing and implementing the HLS(Http Live Streaming) transmitter based embedded linux which is operated easily and cheap and lower power, portable in all networks and client environments compared to exist video live streaming transmitters. We design the developed HLS transmitter hardware using the Arm11 core and then porting the Embedded Linux OS(Operating System) and implementing the HLS protocol using the open source FFmpeg and Segmenter. For proving the performance of developed HLS transmitter, we make the testing environment for testing the performance of HLS transmitter including the notebook, iPhone, android Phone, Notebook and then analysis the received video in the client displayer. In this paper, we suggest the developed HLS transmitter performance data values higher than the Apple company's HLS recommended specification values and the picture of developed HLS transmitter operation in the testing environment. The application field of this paper result is that the man who works in the emergency situation take HLS and transmit the live emergency situation to the head quarter using this portable HLS.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.21-26
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• 2015

In this paper, we propose a system which can detect the smoke in real time from the high-quality IP camera. For real-time processing, open directly the RTSP streams transmitted from the IP camera using the library FFmpeg as opening a video file. To recognize smoke, color information and morphological characteristics of smoke, as well as the dynamic characteristics of the smoke also considered for candidate regions. To combine the characteristics of the various smoke effectively, the Adaboost algorithm, was used as the boosting algorithm finally. Through the experiments with input videos from IP camera, the proposed algorithms were useful to detect smokes.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.11
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• pp.43-53
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• 2010

Wide deployment of high resolution video services leads to active studies on high speed video processing. Especially, prevalent employment of multi-core systems accelerates researches on high resolution video processing based on parallelization of multimedia software. In this paper, we propose a novel parallel H.264/AVC decoding scheme on a multi-core platform. Parallel H.264/AVC decoding is challenging not only because parallelization may incur significant synchronization overhead but also because software may have complicated dependencies. To overcome such issues, we propose a novel approach called Multi-Threaded Parallelization(MTP). In MTP, to reduce synchronization overhead, a separate thread is allocated to each stage in the pipeline. In addition, an efficient memory reuse technique is used to reduce the memory requirement. To verify the effectiveness of the proposed approach, we parallelized FFmpeg H.264/AVC decoder with the proposed technique using OpenMP, and carried out experiments on an Intel Quad-Core platform. The proposed design performs better than FFmpeg H.264/AVC decoder before the parallelization by 53%. We also reduced the amount of memory usage by 65% and 81% for a high-definition(HD) and a full high-definition(FHD) video, respectively compared with that of popular existing method called 2Dwave.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.143-149
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• 2018

This paper presents an implementation of a streaming system which can forward live video stream to multiple users from a Phantom4, which is a drone made by DJI. We constructed the streaming server on Raspberry Pi 3 board for high mobility. Also We implemented the system so that the video stream can be played on any devices if the HTML5 standard web browser is utilized. We compiled C codes of FFmpeg open sources and installed in the Raspberry Pi3 as the streaming server and developed a Java application to execute as the integrated server that controls the other softwares on the streaming server. Also we developed an Android application which receives the live video stream from the drone and sends the streaming server continuously. The implemented system in this paper can successfully stream the live video on 24 frames per second at the resolution of 148x112 in considering the low hardware throughput of the streaming server.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.41-52
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• 2011

It is important to reduce computational complexity of de-blocking filter for real-time implementation, because it accounts for a great part of total computational complexity of the decoder. Because there are a lot of conditional branches and memory accesses in a decoding loop, it is not easy to speed up the de-blocking filter. Therefore, this paper presents a new algorithm of de-blocking filter minimizing conditional branches and memory accesses. The proposed structure of de-blocking filter enables filter operation to parallelize by software pipelining. The proposed optimization method was implemented on a TMS320DM6467 EVM board and we achieved approximately 46% cycle reduction, compared with that of FFmpeg.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1743-1749
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• 2015

As smartphones are rapidly supplied, users can easily access video contents anywhere, anytime. So recently, demands for the ability to create one's own mash-up video have been increasing and various video mash-up programs appear to reflect those needs. But, because most existing video mash-up programs can mash up only stored video files, the ability to mash up many videos is limited for smartphones that have restricted memory. In this paper, we have developed a video mash-up application that can easily mash up not only stored videos, but also videos found by chance over the network to make one's own videos.