• Title/Summary/Keyword: content features

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An Efficient Video Retrieval Algorithm Using Key Frame Matching for Video Content Management

  • Kim, Sang Hyun
    • International Journal of Contents
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    • v.12 no.1
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    • pp.1-5
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    • 2016
  • To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

Interactive Spatial Augmented Reality Book on Cultural Heritage of Myanmar

  • Hta, Aye Chan Zay;Lee, Yunli
    • Journal of information and communication convergence engineering
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    • v.18 no.2
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    • pp.69-74
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    • 2020
  • Myanmar, also known as Burma, has a rich cultural heritage, and its historical tourist attractions well known around the world. Therefore, we designed and developed an interactive spatial augmented reality (iSAR) book on the cultural heritage of Myanmar. This iSAR book has total of 18 pages with rich media content including videos, animations, audio, and images featuring the cultural heritage of Myanmar in a digital format. In addition to virtual content, navigational features such as virtual buttons and touch-based hand gestures were implemented using Leap Motion and VVVV. Therefore, the developed iSAR book allows virtual content and navigational features to merge seamlessly into a physical book. Five participants were recruited to evaluate the prototype iSAR book, and interviews were conducted to gather their feedback based on its immersive qualities. Thus, the developed iSAR book on Myanmar effectively shares the cultural heritage of Myanmar, and ultimately allows users to explore and gain more insight into the country.

Feature Analysis and Detection Techniques for Piracy Sites

  • Choi, Seul-Ki;Kwak, Jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.2204-2220
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    • 2020
  • In recent years, digital content has become easily accessible because of internet technology. Representative examples of such digital content include various types, such as music, TV, (program, sport, drama etc.) and films. However, there are cases where internet technology is used in illegal ways without the authorization of the copyright holder for digital content. Such actions have a direct impact on copyright owners' profits and further affect the development of the digital culture industry adversely. Therefore, in this study, we analyze features to detect piracy sites that cause copyright infringement. Further, we develop a piracy site detection crawler based on these features and present the analysis of its performance.

Comparative Analysis of AI Painting Using [Midjourney] and [Stable Diffusion] - A Case Study on Character Drawing -

  • Pingjian Jie;Xinyi Shan;Jeanhun Chung
    • International Journal of Advanced Culture Technology
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    • v.11 no.2
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    • pp.403-408
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    • 2023
  • The widespread discussion of AI-generated content, fueled by the emergence of consumer applications like ChatGPT and Midjourney, has attracted significant attention. Among various AI applications, AI painting has gained popularity due to its mature technology, user-friendly nature, and excellent output quality, resulting in a rapid growth in user numbers. Midjourney and Stable Diffusion are two of the most widely used AI painting tools by users. In this study, the author adopts a perspective that represents the general public and utilizes case studies and comparative analysis to summarize the distinctive features and differences between Midjourney and Stable Diffusion in the context of AI character illustration. The aim is to provide informative material forthose interested in AI painting and lay a solid foundation for further in-depth research on AI-generated content. The research findings indicate that both software can generate excellent character images but with distinct features.

Improvement of Content-based Image Retrieval by Considering Image Editing Effect (영상편집효과를 고려한 내용기반 영상 검색의 개선에 관한 연구)

  • Kang Seok-Jun;Bae Tae-Meon;Kim Ki-Hyun;Han Seung-Wan;Jeong Chi-Yoon;Nam Tae-Yong;Ro Yong-Man
    • Journal of Korea Multimedia Society
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    • v.9 no.5
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    • pp.564-575
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    • 2006
  • With the rapid increase of the number of multimedia contents, people consume a lot of multimedia contents through various distribution channels. Content-based image retrieval uses visual features that represent the contents of images. And users can retrieve or filter images based on the contents of the images using the features. But, the editing of the multimedia contents distorts the original visual features of the multimedia contents, thereby the performance of content-based image retrieval system could be lowered. In this paper, we describe the image editing effects that lower the performance of the retrieval system and propose algorithms that can remove the image editing effect and improve content-based image retrieval system.

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Image Content Modeling for Meaning-based Retrieval (의미 기반 검색을 위한 이미지 내용 모델링)

  • 나연묵
    • Journal of KIISE:Databases
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    • v.30 no.2
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    • pp.145-156
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    • 2003
  • Most of the content-based image retrieval systems focuses on similarity-based retrieval of natural picture images by utilizing color. shape, and texture features. For the neuroscience image databases, we found that retrieving similar images based on global average features is meaningless to pathological researchers. To realize the practical content-based retrieval on images in neuroscience databases, it is essential to represent internal contents or semantics of images in detail. In this paper, we present how to represent image contents and their related concepts to support more useful retrieval on such images. We also describe the operational semantics to support these advanced retrievals by using object-oriented message path expressions. Our schemes are flexible and extensible, enabling users to incrementally add more semantics on image contents for more enhanced content searching.

Content-based Image Retrieval by Extraction of Specific Region (특징 영역 추출을 통한 내용 기반 영상 검색)

  • 이근섭;정승도;조정원;최병욱
    • Proceedings of the IEEK Conference
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    • 2001.06c
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    • pp.77-80
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    • 2001
  • In general, the informations of the inner image that user interested in are limited to a special domain. In this paper, as using Wavelet Transform for dividing image into high frequency and low frequency, We can separate foreground including many data. After calculating object boundary of separated part, We extract special features using Color Coherence Vector. According to results of this experiment, the method of comparing data extracting foreground features is more effective than comparing data extracting features of entire image when we extract the image user interested in.

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Color Image Retrieval Using Block-based Classification (블록단위 특성분류를 이용한 컬러영상 검색)

  • 류명분;우석훈;박동권;원치선
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1996.06a
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    • pp.63-66
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    • 1996
  • In this paper, we propose a new content-based color image retrieval algorithm. The algorithm makes use of two features; colors as global features and block classification results as local features. More specifically, we obtain R, G, B color histograms and classify nonoverlapping small image blocks into texture, monotone, and various edges, then using these histograms and classification results were make a similarity measure. Experimental results show that retrieval rate of the proposed algorithm is higher than the previous method.

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Feature Extraction Of Content-based image retrieval Using object Segmentation and HAQ algorithm (객체 분할과 HAQ 알고리즘을 이용한 내용 기반 영상 검색 특징 추출)

  • 김대일;홍종선;장혜경;김영호;강대성
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.453-456
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    • 2003
  • Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.

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Design and Implementation of the Video Query Processing Engine for Content-Based Query Processing (내용기반 질의 처리를 위한 동영상 질의 처리기의 설계 및 구현)

  • Jo, Eun-Hui;Kim, Yong-Geol;Lee, Hun-Sun;Jeong, Yeong-Eun;Jin, Seong-Il
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.3
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    • pp.603-614
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    • 1999
  • As multimedia application services on high-speed information network have been rapidly developed, the need for the video information management system that provides an efficient way for users to retrieve video data is growing. In this paper, we propose a video data model that integrates free annotations, image features, and spatial-temporal features for video purpose of improving content-based retrieval of video data. The proposed video data model can act as a generic video data model for multimedia applications, and support free annotations, image features, spatial-temporal features, and structure information of video data within the same framework. We also propose the video query language for efficiently providing query specification to access video clips in the video data. It can formalize various kinds of queries based on the video contents. Finally we design and implement the query processing engine for efficient video data retrieval on the proposed metadata model and the proposed video query language.

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