• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.656-665
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• 2000

A critical issue in the performance of a video-on-demand system is the I/O bandwidth required in order to satisfy client requests. Several approaches: batching, bridging, piggybacking are used ot reduce the I/O demand on the video server through sharing. Piggybacking is the policy for altering display rates of requests in progress fro the same object, for the purpose of merging their corresponding I/O streams into a single stream, which can serve the entire group of merged requests. In this paper, we propose a new policy called an adaptive reservation-based piggybacking that dynamically reserves the I/O stream capacity of video server for popular videos according to video server loads to immediately schedule the requests for popular videos. The performance of the proposed policy is evaluated through simulations, and is compared with that of simple piggybacking. As the result, we know that the adaptive reservation-based piggybacking provides better service probability, average waiting time and percentages saving in frames than simple piggybacking.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.155-158
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• 2005

본 논문에서는 MPEG 의 멀티미디어 응용 표준인 MAF(Multimedia Application Format)를 기반으로, 효율적인 비디오 콘텐츠의 검색 및 활용을 위한 통합 미디어 구조, 즉 비디오 MAF 를 제안한다. 제안하는 비디오 MAF 는 ISO 미디어 포맷을 기반으로 하고 단일의 비주얼 스트림과 다중 음성을 지원하기 위한 다수의 오디오 스트림, 내용기반의 정보를 포함하는 메타데이터, 그리고 비디오 콘텐츠의 대표 이미지를 동시에 포함하는 구조이다. 제안하는 파일포맷의 유용성을 검증하기 위해 비디오 MAF 로 생성 및 해석할 수 있는 부호기(encoder)와 복호기(decoder)를 설계하고 구현하여, 통합 미디어에 내재된 메타데이터를 이용한 효율적인 검색과 멀티트랙의 오디오 스트림을 활용한 다중 음성에 대한 지원이 가능함을 확인하였다. 또한 내재된 대표이미지는 비디오 콘텐츠에 대한 브라우징이 효과적으로 활용됨을 확인하였다.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.110-114
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• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.253-256
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• 2006

본 논문은 사용자의 인터랙션(user interaction)을 고려하여, 사용자가 관심을 가지는 영역에 대해서 최적화된 비디오 콘텐츠를 제공받을 수 있는 비디오 서비스 시스템을 제안한다. 본 논문에서 제안하는 사용자 인터랙티브티를 고려한 서비스 시스템은 SVC(Scalable Video Coding)의 다중 ROI를 사용한다. 또한 제안된 시스템에서는 다양한 방식의 비디오 품질과, 다중 ROI에 대한 선택 과정에서 콘텐츠 소비 주체와 시스템간의 쌍방향 제어 수단을 개발하고 콘텐츠의 관심 영역 지정 과정에서 사용자의 인터렉션 정보를 이용하는 방법을 제안한다. 제안하는 시스템의 유효성을 테스트하기 위해 사용자의 인터랙션에 의해 변환하는 SVC 콘텐트를 만들었고, 사용자 단말에 인터렉션 기능으로 SVC 콘텐츠를 디코딩하는 시스템을 구현하여 유용성을 검증하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.15-20
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• 2002

The frame coding inside the screen for a video coder has a big influence on the quality of the whole frame. The standardized video coder uses DCT, however it can give rise to a low image quality due to the blocking effect at low bit rate. This paper proposes a video coding method for an image quality improvement in human visual aspects. With the proposed method, the perceptual weight is coded with SPIHT and VLC by applying it into the frame and the visual noises are eliminated.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.250-252
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• 2022

As immersive video contents have started to emerge in the commercial market, research on it is required. For this, efficient coding methods for immersive video are being studied in the MPEG-I Visual workgroup, and they released Test Model for Immersive Video (TMIV). In current TMIV, the patches are packed into atlas in order of patch size. However, this simple patch packing method can reduce the coding efficiency in terms of 2D encoder. In this paper, we propose patch packing method which pack the patches into atlases by using the similarity of each patch for improving coding efficiency of 3DoF+ video. Experimental result shows that there is a 0.3% BD-rate savings on average over the anchor of TMIV.

• ETRI Journal
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• v.32 no.6
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• pp.881-890
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• 2010

Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms; for example, a person smoking in a room may trigger a typical fire alarm system. In order to manage false alarms of conventional fire detection systems, a computer vision-based fire detection algorithm is proposed in this paper. The proposed fire detection algorithm consists of two main parts: fire color modeling and motion detection. The algorithm can be used in parallel with conventional fire detection systems to reduce false alarms. It can also be deployed as a stand-alone system to detect fire by using video frames acquired through a video acquisition device. A novel fire color model is developed in CIE $L^*a^*b^*$ color space to identify fire pixels. The proposed fire color model is tested with ten diverse video sequences including different types of fire. The experimental results are quite encouraging in terms of correctly classifying fire pixels according to color information only. The overall fire detection system's performance is tested over a benchmark fire video database, and its performance is compared with the state-of-the-art fire detection method.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.137-141
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• 1997

In this study, in order to improve visualization and enhance the ability of the surgeon to perform delicate endoscopic surgery, three dimensional endoscopic system is designed. These 3D systems have our features of stereoendoscopic image processing: real time image capture and retrieve; presentation of left and right image on a single monitor; separable processing of the left and right eye images; coding of the 3D endoscopic video. For 3D endoscopic video coding, three approaches are presented based on interlaced picture structure, side-field format structure, and simulcast technique. Experimental results and performances comparisons are presented and analyzed or these approaches. Digital video coding techniques are presented or 3D endoscopic video sequences by means of an MPEG-2 video coding.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.161-169
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• 2011

Recent intelligent video surveillance system asks for development of more advanced technology for analysis and recognition of video data. Especially, machine learning algorithm such as Support Vector Machine (SVM) is used in order to recognize objects in video. Because SVM training demands massive amount of computation, parallel processing technique is necessary to reduce the execution time effectively. In this paper, we propose a parallel processing method of SVM training with a multi-core processor. The results of parallel SVM on a 4-core processor show that our proposed method can reduce the execution time of the sequential training by a factor of 2.5.