• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.169-177
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• 2014

It is essential to support the image and video analysis technology such as motion detection since the DVR and NVR storage were adopted in the real time visual surveillance system. Especially the network camera would be popular as a video input device. The traditional CCTV that supports analog video data get be replaced by the network camera. In this paper, we present the design and implementation of video surveillance system that provides the real time motion detection by the video storage server. The mobile application also has been implemented in order to provides the retrieval functionality of image analysis results. We develop the video analysis server with open source library OpenCV and implement the daemon process for video input processing and real-time image analysis in our video surveillance system.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.31-40
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• 2021

The multi-channel video streaming system is an essential device for future ground combat vehicles. For the system, the application of digital interfaces is required instead of the direct analog method to support selectable multiple channels. However, due to the characteristics of the digital interfaces that require en/decoding and signal conversion, the system should support the ability to adapt to quality and delay requirements depending on how video data is utilized. To support addressed issue, this study designs and emulates the multi-channel compressed-video streaming system of ground combat vehicle's fire control system based on commercial standards. Using the system, this study analyzes the quality of video according to the rotational speed of the acquisition device and Glass-to-Glass (G2G) delay between video acquisition and display devices according to video compression rates. Through these experiments and analysis, this paper presents the design direction of the system having scalability on the latest technology while providing high-quality video data streaming flexibly.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.115-123
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• 2012

A video analysis system used to detect events in video streams generally has several processes, including object detection, object trajectories analysis, and recognition of the trajectories by comparison with an a priori trained model. However, these processes do not work well in a complex environment that has many occlusions, mirror effects, and/or shadow effects. We propose a new approach to a context-aware video surveillance system to detect predefined contexts in video streams. The proposed system consists of two modules: a feature extractor and a context recognizer. The feature extractor calculates the moving energy that represents the amount of moving objects in a video stream and the stationary energy that represents the amount of still objects in a video stream. We represent situations and events as motion changes and stationary energy in video streams. The context recognizer determines whether predefined contexts are included in video streams using the extracted moving and stationary energies from a feature extractor. To train each context model and recognize predefined contexts in video streams, we propose and use a new ensemble classifier based on the AdaBoost algorithm, DAdaBoost, which is one of the most famous ensemble classifier algorithms. Our proposed approach is expected to be a robust method in more complex environments that have a mirror effect and/or a shadow effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.306-309
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• 2008

A system realization for video surveillance with interframe probability distribution analysis is presented in this paper. The system design is based on a high performance DSP processor, video surveillance is implemented by analyzing interframe probability distribution for scanning objects in a restricted area and the video analysis algorithm is decided for forming a different image from the probability distribution of several frames compressed by the standardized JPEG. The algorithm processing time of D1($720{\times}480$) image per frame is 85ms.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.499-510
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• 2022

This paper introduces a video editing system for senior creator who is not familiar to video editing. Based on video analysis techniques, it provide various information and delete unwanted shot. The system detects shot boundaries based on RNN(Recurrent Neural Network), and it determines the deletion of video shots. The shots can be deleted using shot-level significance, which is computed by detecting focused area. It is possible to delete unfocused shots or motion-blurred shots using the significance. The system detects object and face, and extract the information of emotion, age, and gender from face image. Users can create video contents using the information. Decorating tools are also prepared, and in the tools, the preferred design, which is determined from user history, places in the front of the design element list. With the video editing system, senior creators can make their own video contents easily and quickly.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.11-16
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• 1997

This paper describes the grenade counting system developed for DPICM submunition analysis using the infrared video streams, and its some video stream processing technique. The video stream data processing procedure consists of four sequences; Analog infrared video stream recording, video stream capture, video stream pre-processing, and video stream analysis including the grenade counting. Some applications of this algorithms to real bursting test has shown the possibility of automation for submunition counting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.90-95
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• 2002

This thesis is aiming at analysis and implementing Distance Video Lecturing System to guarantee the high quality in service through using less Network resource. Most of the usual Distance Video Lecturing System has been designed not in the system of Multiuser Conference but Point-to-Point. But from now on Distance Video Lecturing System is to be demanded on not only the expansion to Multiuser Distance Video Lecturing System, but high quality in service for users. To solve these problems, the Multicast Transmission Technology as the dimension of Network as well as highly efficient, advanced Compression Technology should be applied to Video Conference System in company with the expansion of Network bandwidth. The system suggested in this thesis is to help to offer an application service as Distance Video Lecturing System that will make popular on the basis of the character that the next generation Internet will be high speed Network.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.384-389
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• 2008

Recently, the necessity of systems which effectively store and retrieve video data has increased. Conventional video retrieval systems retrieve data using menus or text based keywords. Due to the lack of information, many video clips are simultaneously searched, and the user must have a certain level of knowledge to utilize the system. In this paper, we suggest a natural language based conversational video retrieval system that reflects users' intentions and includes more information than keyword based queries. This system can also retrieve from events or people to their movements. First, an event database is constructed based on meta-data which are generated by domain analysis for collected video in an office environment. Then, a script database is also constructed based on the query pre-processing and analysis. From that, a method to retrieve a video through a matching technique between natural language queries and answers is suggested and validated through performance and process evaluation for 10 users The natural language based retrieval system has shown its better efficiency in performance and user satisfaction than the menu based retrieval system.

• Journal of Broadcast Engineering
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• v.9 no.2
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• pp.164-173
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• 2004

In this paper, we propose a system that can analyze appearance interval of casts by detecting and recognizing casts in broadcasting videos. The cast is one of the most important characteristics in broadcasting videos such as drama and sports. In this paper, we propose the ACAV(Automatic Cast-list Analysis in Videos) system that analyzes cast-list automatically in video. The ACAV system consists of FAGIS(FAce reGIStration) which registers detected faces into the face DB and FACOG(FAce reCOGnition) that analyses the cast-list in video sequence using the face DB. We evaluate performance of the ACAV system by comparing with FaceIt, one of the most well-known commercial systems for the cast-list analysis. The ACAV shows face detection and recognition rates of 84.3% and 75.7% that are about 30% and 27.5% higher than those of FaceIt, respectively. The ACAV system can be applied to mass broadcasting videos management system for broadcasters and video management system of PVR(Personal Video Recorder) and mobile phone for the public.

• ETRI Journal
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• v.27 no.6
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• pp.806-809
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• 2005

The main goal of this research is automatic video analysis using a face recognition technique. In this paper, an automatic video management system is introduced with a variety of functions enabled, such as index, edit, summarize, and retrieve multimedia data. The automatic management tool utilizes MPEG-7 visual descriptors to generate a video index for creating a summary. The resulting index generates a preview of a movie, and allows non-linear access with thumbnails. In addition, the index supports the searching of shots similar to a desired one within saved video sequences. Moreover, a face recognition technique is utilized to personalbased video summarization and indexing in stored video data.