• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1257-1264
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• 2017

In video content watching service, when a user requests video content, the content server has to transmit the entire video to the client for watching. This transmission delay increases as the size of video content increases. In order to solve the transmission delay problem, a prefetching technique can be used in which a video content to be watched by a user is predicted and transmitted to a client before the user requests it. In this paper, we propose a prefetching system considering multiple indices for video content. In the proposed method, video content to be prefetched is selected by comprehensively analyzing the order relation index indicating the order of viewing the videos of the users, the similarity index between the video contents, and the popularity index reflecting the viewing frequency of the video content. Experimental results show that the maximum accuracy is achieved when prefetching uses only the order relation index for movie contents.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1109-1118
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• 1998

Recently, much attention has been focused on video databases. Video documents also have a hierarchical logical structure like text documents. By exploiting this structure using structure queries, users can obtain greater benefits than by using only content queries. In order to process structure queries efficiently, an index structure supporting fast video element access must be provided. However, there has been little attention to the index structure for video documents. In this paper, we present a tree-structured video document model and a new inverted index structure for video documents. We evaluate the storage requirement and the disk access time of the scheme and present the analytical results.

• International Journal of Contents
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• v.5 no.4
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• pp.51-54
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• 2009

In huge video databases, the effective video content indexing method is required. While manual indexing is the most effective approach to this goal, it is slow and expensive. Thus automatic indexing is desirable and recently various indexing tools for video databases have been developed. For efficient video content indexing, the similarity measure is an important factor. This paper presents new similarity measures between frames and proposes a new algorithm to index video content using Kullback-Leibler distance defined between two histograms. Experimental results show that the proposed algorithm using Kullback-Leibler distance gives remarkable high accuracy ratios compared with several conventional algorithms to index video content.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1052-1059
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• 2016

Video-on-Demand(VoD) is one of the most popular media streaming which attracted many researchers' attention. VMesh is one of the most cited works in the field of the VoD system. VMesh is proposed to solve the problem of random seeking functionality. However, a large number of the DHT(Distributed Hash Table) searches in VMesh is sill the main problem which needs to be solved. In order to reduce the number of the DHT searches, the clustered segment index(CSI) scheme is proposed. In this scheme, the video segments are divided into clusters. The segment information of the video segments, which are clustered into the same cluster, are stored in the same clustered segment index that can be searched by using the hash key. Each peer also can request the required segments by using this clustered segment index. The experiment results show that the number of the DHT searches in the proposed scheme is less than that of VMesh even in case of peers leave and join the network or peers perform the fast forward/backward operations.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.891-898
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• 2004

An effective video indexing is required to manipulate large video databases. Most algorithms for video indexing have been commonly used histograms, edges, or motion features. In this paper, we propose an efficient algorithm using the luminance projection for video retrieval. To effectively index the video sequences and to reduce the computational complexity, we use the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed video indexing and video retrieval algorithm yields the higher accuracy and performance than the conventional algorithm.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.697-701
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• 2010

The numbers of digital video cameras are fast increased. Accordingly, digital video data management is becoming more important. Efficient storing method and fast browsing method still remains to be one of significant issue. In this paper, an optimized data storing process without losing information and an organized appearance features indexing method are proposed. Also, the data removing policy could be used to reduce large amount of space and it facilitates fast sequential search. The appearance features index constructs key information of moving objects to answer queries about what people are doing, particularly when, where and who they move. The evaluation results showed better performance in the transfer time and the saving in storage space.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.132-135
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• 2009

The video similarity measure is very important factor to index and to retrieve for video data. In this paper, we propose the luminance projection model to measure the video similarity efficiently. Most algorithms for video indexing have been commonly used histograms, edges, or motion features, whereas in this paper, the proposed algorithm is employed an efficient measure using the luminance projection. To index effectively the video sequences and to decrease the computational complexity, we calculate video similarity using the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed luminance projection model yields the remarkable accuracy and performance than the conventional algorithm.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.2
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• pp.185-193
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• 2011

The purpose of this study was to determine the effects of nutrient intake, screen time (television viewing and computer and/or video games) and physical activity on obesity in preschool children. Recruitment began in January 2008 by distributing letters to mothers who had children aged 6 years enrolled in daycare. Dietary intakes were obtained from the children's mothers, using the 24-hour recall method. The average height and weight of the children were 114.2 cm and 20.3 kg, respectively. Mean age, body weight, height and Kaup index were not significantly different between groups consisting of boys or girls. Assessment by the Kaup index showed that 14.0% of children were underweight, 69.0% were normal weight, 13.0% were overweight, and 4% were obese. The daily intakes of calcium, potassium, fiber, and folic acid in the group of boys were 77.7%, 58.5%, 80.4% and 88.9% respectively. as compared with the DRIs. The daily intakes of calcium, potassium, fiber, and folic acid in the group of girls were 77.7%, 58.5%, 80.4% and 88.9%, respectively. as compared with the DRIs. Intakes of protein, phosphorus, iron, zinc, vitamin A, thiamin, riboflavin, niacin, vitamin C, and vitamin E were higher than the DRIs. There were no difference among 3 groups (underweight, normal, overweight) in energy or nutrient intake. Preschool children with screen time (TV viewing and computer and/or video games use time) of >2 hours per day had significantly higher Kaup index values, and intakes of energy, carbohydrate, folic acid and zinc. In conclusion, preschool children with reported screen time (TV viewing and computer and/or video games use time) of >2 hours per day were fatter. Therefore, we need further investigate the relation between diet and screen time in preschool children to improve future nutrition education programs. Further studies are required to explore the effects of food intake and screen time (TV viewing and computer and/or video games use time) over a longer period of time.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.610-617
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• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.