• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.65-71
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• 2005

With the rapid improvement of the internet and information technology, digital contents containing knowledge and information resource is circulated through the internet. A circulation system based on a standardized identifier is required to share this kind of information, generated from seminars and workshops conducted in the area of science and technology and saved in the form of digital video contents. The main objective of this study is on constructing an information circulation system based on the KOI identifier to effectively share the digital video contents produced from seminars and workshops related to the area of science and technology. Furthermore, the overview and status of a standardized identifier, and the functional aspects of the system such as the methods to apply the KOI identification system on the subject and its slides of digital video contents, a digital video contents management system, a centralized identifier management system, and the methods applied for the search of digital video metadata have been suggested to support construction of the information circulation system.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.3
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• pp.213-234
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• 2020

The purpose of this study is to lay the foundation for the construction of an identification system by proposing descriptive items that can identify the creators who participated in the production of broadcasting video records. In order to uniquely identify the creators of broadcasting video records, a total of seven descriptive categories, including name, gender, date of birth, name identifier system, nationality, affiliated agencies, and major fields, were organized into three categories: individual, affiliation, and role. These categories were classified and categorized into two stages. Based on the proposed structure, a total of 10 basic facets and 14 sub-facets were constructed to establish a faceted structure for identifying the creators of broadcasting video records.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.262-268
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• 2017

Intelligent video surveillance systems have been developed to monitor global areas and find specific target objects using a large-scale database. However, person re-identification presents some challenges, such as pose change and occlusions. To solve the problems, this paper presents an improved person re-identification method using sparse representation and saliency-based dictionary construction. The proposed method consists of three parts: i) feature description based on salient colors and textures for dictionary elements, ii) orthogonal atom selection using cosine similarity to deal with pose and viewpoint change, and iii) measurement of reconstruction error to rank the gallery corresponding a probe object. The proposed method provides good performance, since robust descriptors used as a dictionary atom are generated by weighting some salient features, and dictionary atoms are selected by reducing excessive redundancy causing low accuracy. Therefore, the proposed method can be applied in a large scale-database surveillance system to search for a specific object.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.201-212
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• 2011

This study examines the potentials of realistic controller and point-of-view to affect users' arousal, valence, identification and engagement. While media researchers have advocated the role of realistic controller and point-of-view as a possible contributor to psychological reactions of playing video game, this claim is based on a relatively small number of empirical studies. Collegiate subjects took part in an experimental investigation manipulation the level of controller realism(gamepad vs. steering wheel) and point-of-view(first person vs. third person). Results of the study showed the influence of controller realism and point-of-view on arousal, identification and engagement, and the implication of the findings are discussed.

• Smart Structures and Systems
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• v.23 no.4
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.107-115
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• 2011

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.

• 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.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• Journal of IKEEE
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• v.14 no.4
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• pp.297-304
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• 2010

This paper presents a link layer design of DisplayPort interface with a state machine based on packet processing. The DisplayPort link layer provides isochronous video/audio transport service, link service, and device service. The merged video, audio main link, and AUX channel controller are implemented with 7,648 LUTs(Loop Up Tables), 6020 register, and 821,760 of block memory bits synthesized using a FPGA board and it operates at 203.32MHz.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.229-235
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• 2019

Due to the development of video and optical technology today, video equipments are being used in a variety of fields such as identification, security maintenance, and factory automation systems that generate products. In this paper, we investigate an algorithm that effectively recognizes an experimental object in an input image with a partial problem due to the mechanical problem of the input imaging device. The object recognition algorithm proposed in this paper moves and rotates the vertices constituting the outline of the experimental object to the positions of the respective vertices constituting the outline of the DB model. Then, the discordance values between the moved and rotated experimental object and the corresponding DB model are calculated, and the minimum discordance value is selected. This minimum value is the final discordance value between the experimental object and the corresponding DB model, and the DB model with the minimum discordance value is selected as the recognition result for the experimental object. The proposed object recognition method obtains satisfactory recognition results using only partial information of the experimental object.