• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.212-217
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• 2007

As a preliminary study for the development of electrical stimulation strategy of artificial retina, we set up a method fur the reconstruction of input intensity variation from retinal ganglion cell(RGC) responses. In order to estimate light intensity variation, we used an optimal linear filter trained from given stimulus intensity variation and multiple single unit spike trains from RGCs. By applying ON/OFF stimulation(ON duration: 2 sec, OFF duration: 5 sec) repetitively, we identified three functional types of ganglion cells according to when they respond to the ON/OFF stimulus actively: ON cell, OFF cell, and ON-OFF cell. Experiments were also performed using a Gaussian random stimulus and a binary random stimulus. The input intensity was updated once every 90 msec(i. e. 11 Hz) to present the stimulus. The result of reconstructing 11 Hz Gaussian and binary random stimulus was not satisfactory and showed low correlation between the original and reconstructed stimulus. In the case of ON/OFF stimulus in which temporal variation is slow, successful reconstruction was achieved and the correlation coefficient was as high as 0.8.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1469-1483
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• 2004

We propose a packet scheduling algorithms for streaming media. We assume that the receiver periodically reports back the channel throughput. From the original video data, the importance level of a video packet is determined by its relative position within its group of pictures, taking into account the motion-texture discrimination and temporal scalability. Thus, we generate a number of nested substreams. Using feedback information from the receiver and statistical characteristics of the video, we model the streaming system as a queueing system, compute the run-time decoding failure probability of a Same in each substream based on effective bandwidth approach, and determine the optimum substream to be sent at that moment in time. Since the optimum substream is updated periodically, the resulting sending order is different from the original playback order. From experiments with real video data, we show that our proposed scheduling scheme outperforms the conventional sequential sending scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.836-845
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• 2002

Video summary is one of the tools which can provide the fast and effective browsing for a lengthy video. Video summary consists of many key-frames that could be defined differently depending on the video genre it belongs to. Consequently, the video summary constructed by the uniform manner might lead into inadequate result. Therefore, identifying the video genre is the important first step in generating the meaningful video summary. We propose a new method that can classify the genre of the video data in MPEC compressed bit-stream domain. Since the proposed method operates directly on the compressed bit-stream without decoding the frame, it has merits such as simple calculation and short processing time. In the proposed method, only the visual information is utilized through the spatial-temporal analysis to classify the video genre. Experiments are done for 6 genres of video: Cartoon, commercial, Music Video, News, Sports, and Talk Show. Experimental result shows more than 90% of accuracy in genre classification for the well -structured video data such as Talk Show and Sports.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.837-842
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• 2008

Any errors that are generated in the channels and networks distort the video quality and are propagated in both the spatial and temporal domains. In particular, header errors ran result in serious visual degradation of the output video encoding/decoding schemes that can make an error resilient compressed bit-stream in error prone environments, such as mobile networks. In this paper, we proposes an header error resilience method that consider the activity of macroblock in video bitstream syntex. The extract of header error repaetedly embeds the header parameters into the least significant bits(LSB) of the quantized DCT coefficients prior to VLC. Experimental results show that the proposed error resilience method restores good image quality despite the detected error on header parameters.

• Journal of Broadcast Engineering
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• v.11 no.3 s.32
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• pp.363-378
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• 2006

The Digital Multimedia Broadcasting(DMB) system is developed to offer high quality audio-visual multimedia contents to the mobile environment. The system adopts MPEG-4 standard for the main video, audio and other media format. It also adopts the MPEG-4 scene description for interactive multimedia contents. The animated and interactive contents can be actualized by BIFS(Binary Format for Scene), the binary format for scene description that refers to the spatio-temporal specifications and behaviors of the individual objects. As more interactive contents are, the scene description is also needed more high bitrate. However, the bandwidth for allocating meta data such as scene description is restrictive in mobile environment. On one hand, the DMB terminal starts demultiplexing content and decodes individual media by its own decoder. After decoding each media, rendering module presents each media stream according to the scene description. Thus the BIFS stream corresponding to the scene description should be decoded and parsed in advance of presenting media data. With these reason, the transmission delay of BIFS stream causes the delay of whole audio-visual scene presentation although the audio or video streams are encoded in very low bitrate. This paper presents the effective optimization technique for adapting BIFS stream into expected MPEG-2 TS bitrate without any bandwidth waste and avoiding the transmission delay of the initial scene description for interactive DMB contents.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.113-121
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• 2012

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.