• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.97-100
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• 1995

In transmission of image sequences over ATM networks, the packet loss problem and channel sharing efficiency are important. As a possible solution two-layer video coding methods have been proposed. These methods transmit video information over the network with different levels of protection with respect to packets loss. In this paper, a two-layer coding method using pyramid structure is proposed and several realizations of two-layer video coding methods are presented and their performances are compared.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.77-81
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• 1996

In order to conform to the needs of effective program production in multimedia era, we are studying Desk Top Program Production system. With the DTPP, users can easily produce multimedia program including video, sound, and ancillary data, and freely handle video images synthesizing video components retrieved from video database. This paper describes the new program production system, DTPP and its key technologies such as cooperative program production via multimedia network, indexing and utilization of attribute information of images, and image segmentation and spatio-temporal editing.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.143-148
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• 1995

In this paper, we describe a fast 3D video segmentation method using mathematical morphology. The proposed 3D video segmentation algorithm is composed of intra-frame segmentation step and inter-frame segmentation step. In the intra-frame segmentation step, the first frame is segmented using the fast hierarchical segmentation method. Then, in the inter-frame segmentation step, the next frames are segmented using markers that are extracted from the difference of previous segmentation result and simplified present image. Experimental results show that the proposed method has more fast structure and is suitable for video segmentation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.374-375
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• 2017

As the distribution of image contents is activated, users can easily access image contents through various routes and media.In this paper, we propose a new virtual reality (VR) system, which is based on the development of IT technology, in order to prepare for the fourth industrial revolution era.We propose a method of producing educational video contents that combines maximized virtual reality.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.623-625
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• 2003

공간정보와 멀티미디어가 긴밀히 결합된 새로운 형태의 지리정보 환경이 미디어 지리정보시스템(MediaGIS)이다. 비디오 지리정보시스템(VideoGIS)은 미디어 지리정보시스템의 한 예로서 공간정보와 비디오와의 결합과 상호작용에 중점을 두고 있다. 본 논문에서 제시한 지오 비디오(GeoVideo)는 비디오를 기반으로 공간정보의 조회, 검색, 분석 등이 가능한 최초의 비디오 지리정보시스템이다. 지오 비디오는 기존의 인위적이고 함축적이고 그래픽적인 패러다임에서 자연적이고 사실적이고 이미지적인 패러다임으로의 변화의 의미를 지닌다. 본 논문에서는 비디오와 공간정보의 결합에 대해 자세히 논의하고 시스템 구성 방법에 있어서의 고려사항 등에 관해서 논의하기로 한다.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.50-55
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• 2013

This article presents a simple and reasonable in-service, real-time, and continuous single-ended objective video quality assessment model for DTV broadcasting using a multiburst signal at the bottom of the transient effect area, similar to Vertical Interval Test Signals. The issue of in-service video-quality monitoring in DTV broadcasting is addressed, and an effective method of quality monitoring is presented. The proposed method is also implemented and tested in a range of situations using a simulated HDTV broadcasting network.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.52-54
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• 2021

In this paper we propose a method predict whether a video frame contains motion according to the invoking situation of the coding unit mode in HEVC. The motion prediction of video frames is conducive for use in video compression and video data extraction. In the existing technology, motion prediction is usually performed by high complexity computer vision technology. However, we proposed to analyze the motion frame based on HEVC coding unit mode which does not need to use the static background frame. And the prediction accuracy rate of motion frame analysis by our method has exceeded 80%.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1278-1281
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• 2022

현재 Action classification model은 computational resources의 제약으로 인해 video전체의 frame으로 학습하지 못한다. Model에 따라 다르지만, 대부분의 경우 하나의 action을 학습시키기 위해 보통 많게는 32frame, 적게는 8frame으로 model을 학습시킨다. 본 논문에서는 이 한계를 극복하기 위해 하나의 video의 많은 frame들을 mix-up과정을 거쳐 한장의 frame에 여러장의 frame 정보를 담고자 한다. 이 과정에서 video의 시간에 따른 변화(temporal- dynamics)를 손상시키지 않기 위해 linear mix-up이라는 방법을 제안하고 그 성능을 증명하며, 여러장의 frame을 mix-up시켜 모델의 성능을 향상시키는 가능성에 대해 논하고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.171-174
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• 2022

Weakly-supervised learning is a widely adopted approach in video anomaly detection whereby only video labels are utilized instead of expensive frame-level annotations. Since the success of multi-instance learning (MIL), almost all recent approaches are based on maximizing the margin between the set of abnormal video snippets and those of normal video snippets. In this work, we present a simple contrastive approach for weakly supervised video anomaly detection (WS-VAD) with aims to enhance the performance of existing models. The method is generic in nature and introduces a loss function to encourage attraction of output features from the same video class and repel those from different video classes. Experimental results demonstrate our method can be applied to existing algorithms to improve detection accuracy in public video anomaly dataset.

• Journal of KIISE
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• v.43 no.3
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• pp.370-379
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• 2016

Recently personal media were produced in a variety of ways as a lot of smart devices have been spread and services using these data have been desired. Therefore, research has been actively conducted for the media analysis and recognition technology and we can recognize the meaningful object from the media. The system using the media ontology has the disadvantage that can't classify the media appearing in the video because of the use of a video title, tags, and script information. In this paper, we propose a system to automatically classify video using the objects shown in the media data. To do this, we use a description logic-based reasoning and a rule-based inference for event processing which may vary in order. Description logic-based reasoning system proposed in this paper represents the relation of the objects in the media as activity ontology. We describe how to another rule-based reasoning system defines an event according to the order of the inference activity and order based reasoning system automatically classify the appropriate event to the category. To evaluate the efficiency of the proposed approach, we conducted an experiment using the media data classified as a valid category by the analysis of the Youtube video.