• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.2
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• pp.46-64
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• 2003

The vector shaped object is generally very long (hundreds or thousands of kilometers) and very narrow (10-100 meters). Image mapping techniques and tools for these objects should be totally different from the traditional area-based targets. Acknowledging these unique characteristics of the vector shaped object, a motion picture mapping system has been developed by combining internet GIS technology with airborne video. In particular, integration between airborne video and digital maps took advantage of each component, and enabled the landscape structure to be visualized, interacted with and deployed all on the Web. The motion picture maps provided a completely new means for disseminating information for area-wide landscape in a visual and interactive manner to the general public while digital map with location information revealed successfully the major parameters that influence an area-wide spatial structure in the study area. The remote video approach breaks down the usual concept of image mapping in a conventional cartography. As a result, the research findings have established the new concept of 'internet airborne video mapping for vector shaped object', proposed as an initial aim of this paper. It would playa crucial role in improving the quality of public information service if the mapping system is operationally introduced into the Government since the highly user-friendly moving picture provides a completely new means for disseminating spatia) information for vector shaped object.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.308-317
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• 2022

Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1262-1270
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• 2020

Recently, the smart video surveillance research, which has been receiving increasing attention, has mainly focused on the intruder detection and tracking, and abandoned object detection. On the other hand, research on real-time detection of stolen objects is relatively insufficient compared to its importance. Considering various smart surveillance video application environments, this paper presents two different types of stolen object detection algorithms. We first propose an algorithm that detects theft of statically and dynamically registered surveillance objects using a dual background subtraction model. In addition, we propose another algorithm that detects theft of general surveillance objects by applying the dual background subtraction model and Mask R-CNN-based object segmentation technology. The former algorithm can provide economical theft detection service for pre-registered surveillance objects in low computational power environments, and the latter algorithm can be applied to the theft detection of a wider range of general surveillance objects in environments capable of providing sufficient computational power.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.55-62
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• 2014

In the intelligent video surveillance system, moving objects generally are detected by calculating difference between background and input image. However formation of reliable background is known to be still challenging task because it is hard to cope with the complicated background. In this paper we propose an adaptive background formation algorithm considering stationary object. At first, the initial background is formed by averaging the initial N frames. Object detection is performed by comparing the current input image and background. If the object is at a stop for a long time, we consider the object as stationary object and background is replaced with the stationary object. On the other hand, if the object is a moving object, the pixels in the object are not reflected for background modification. Because the proposed algorithm considers gradual illuminance change, slow moving object and stationary object, we can form background adaptively and robustly which has been shown by experimental results.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3097-3110
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• 1997

As to the recent advances in computer technologies and high-speed networks, telecommunication services and provision of multimedia services will be provided on the basic of a new software architecture adapting networking infrastructure on open information networking architecture. In this paper, the video conference services has been selected as a target service example because it is expected to become one of the most important services on the full service network. In fact, it can be viewed as the basis for providing telecommunication services such as video telephony and video conferencing. This paper presents the prototyping of TINA (Telecommunication Information Networking Architecture) based desktop video conference system using the concepts of session management. The prototyping of desktop video conference system aims at assessing TINA concepts and refinement of the mapping between session graph and connection graph, and provides object modeling methodologies towards distribution and objected-orientation.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.143-152
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• 2008

Nowadays, many investigators are studying various methodologies concerning event expression for semantic retrieval of video data. However, most of the parts are still using annotation based retrieval that is defined into annotation of each data and content based retrieval using low-level features. So, we propose a method of creation of the motion unit and extracting event through the unit for the more semantic retrieval than existing methods. First, we classify motions by event unit. Second, we define semantic unit about classified motion of object. For using these to event extraction, we create rules that are able to match the low-level features, from which we are able to retrieve semantic event as a unit of video shot. For the evaluation of availability, we execute an experiment of extraction of semantic event in video image and get approximately 80% precision rate.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.19-25
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• 2024

This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.

• Journal of IKEEE
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• v.13 no.4
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• pp.1-7
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• 2009

A video segmentation algorithm, which can extract objects even with non-stationary backgrounds, is proposed in this work. The proposed algorithm is composed of three steps. First, we perform an initial segmentation interactively to build the probability density functions of colors per each macro block via kernel density estimation. Then, for each subsequent frame, we construct a coherence strip, which is likely to contain the object contour, by exploiting spatio-temporal correlations. Finally, we perform the segmentation by minimizing an energy function composed of color, coherence, and smoothness terms. Experimental results on various test sequences show that the proposed algorithm provides accurate segmentation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1086-1092
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• 2009

Stereoscopic conversion has been an important and challenging issue for many 3-D video applications. Usually, there are two different stereoscopic conversion approaches, i.e., image motion-based conversion that uses motion information and object-based conversion that partitions an image into moving or static foreground object(s) and background and then converts the foreground in a stereoscopic object. As well, since the input sequence is MPEG-1/2 compressed video, motion data stored in compressed bitstream are often unreliable and thus the image motion-based conversion might fail. To solve this problem, we present the utilization of key-motion that has the better accuracy of estimated or extracted motion information. To deal with diverse motion types, a transform space produced from motion vectors and color differences is introduced. A key-motion is determined from the transform space and its associated stereoscopic image is generated. Experimental results validate effectiveness and robustness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.2120-2130
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• 1998

This paper concerns a design of programmable MPEG decoder for video processing by object unit on network. The decoder can process video data effectively by a embedded controller with stack buffers for supporting OOP (Object-Oriented Programming). The controller offers extended instructions that process several data types including 32bit integer type. In addition to that, we have a vector processor, in this decoder that can execute advanced compensation and prediction by half pixel and SA(Shape Adaptive)-IDCT of MPEG-4. Absolutors and halfers in the vector processor make this architecture extensive to a encoder. We verified the decoder with $0.6\mu\textrm{m}$ 5-Volt CMOS COMPASS library.