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conference on Imaging and Printing in a Web 2.0 World;and multimedia content access - algorithms and systems IV

作者： Shen, Yi Yang, Chunlei Gao, Yuli Fan, Jianping UNC Charlotte Dept Comp Sci Charlotte NC USA HP Labs Multimedia Interact & Understand Lab Palo Alto CA USA

ISBN: (纸本)9780819479334

To crawl large amounts of weakly-tagged images for computer vision tasks such as object detection and scene recognition, it is very important to develop new techniques for tag cleansing and word sense disambiguation (i.e., removing irrelevant images from the crawled results). Based on this observation, a topic network is first generated to characterize both the semantic similarity contexts and the visual similarity contexts between the image topics more sufficiently. The topic network is used to represent the classes of objects and scenes of interest. Second, both the visual similarity contexts between the images and the semantic similarity contexts between their tags are integrated for tag cleansing and word sense disambiguation. By addressing the issues of polysemes and synonyms more effectively, our word sense disambiguation algorithm can determine the relevance between the images and the associated tags more precisely, and thus it can allow us to crawl large-scale weakly-tagged images for computer vision tasks.

关键词： Weakly-tagged images tag cleansing topic network

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Generic and optimized framework for multi-content analysis based on learning approaches

Generic and optimized framework for multi-content analysis b...

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conference on Imaging and Printing in a Web 2.0 World;and multimedia content access - algorithms and systems IV

作者： Besnehard, Quentin Marchessoux, Cedric Kimpe, Tom Barco NV B-8500 Kortrijk Belgium

ISBN: (纸本)9780819479334

During the European Cantata project (ITEA project, 2006-2009), a Multi-content Analysis framework for the classification of compound images in various categories (text, graphical user interface, medical images, other complex images) was developed within Barco. The framework consists of six parts: a dataset, a feature selection method, a machine learning based Multi-content Analysis (MCA) algorithm, a Ground Truth, an evaluation module based on metrics and a presentation module. This methodology was built on a cascade of decision tree-based classifiers combined and trained with the AdaBoost meta-algorithm. In order to be able to train these classifiers on large training datasets without excessively increasing the training time, various optimizations were implemented. These optimizations were performed at two levels: the methodology itself (feature selection / elimination, dataset pre-computation) and the decision-tree training algorithm (binary threshold search, dataset presorting and alternate splitting algorithm). These optimizations have little or no negative impact on the classification performance of the resulting classifiers. As a result, the training time of the classifiers was significantly reduced, mainly because the optimized decision-tree training algorithm has a lower algorithmic complexity. The time saved through this optimized methodology was used to compare the results of a greater number of different training parameters.

关键词： Multi-content analysis machine learning AdaBoost decision trees optimization

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A Novel XML-Based Document Format with Printing Quality for Web Publishing

A Novel XML-Based Document Format with Printing Quality for ...

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conference on Imaging and Printing in a Web 2.0 World;and multimedia content access - algorithms and systems IV

作者： Qiu, Ruiheng Tang, Zhi Gao, Liangcai Yu, Yinyan Peking Univ Inst Comp Sci & Technol Beijing 100871 Peoples R China

ISBN: (纸本)9780819479334

Although many XML-based document formats are available for printing or publishing on the Internet, none of them is well designed to support both high quality printing and web publishing. To address this problem, we propose a novel XML-based document format for web publishing, called CEBX, in this paper. The proposed format is a fixed-layout document with printing quality, which has optimized document content organization, physical structure and protection scheme to support web publishing. There are four noteworthy features of CEBX documents: (1) CEBX provides original fixed layout by graphic units for high quality rendering. (2) The content in CEBX document can be reflowed to fit the display device basing on the content blocks and additional fluid information. (3) XML Document Archiving model (XDA), the packaging model used in CEBX, supports document linearization and incremental edit well. (4) By introducing a segment-based content protection scheme into CEBX, some part of a document can be previewed directly while the remaining part is protected effectively such that readers only need to purchase partial content of a book that they are interested in. This will be very helpful to document distribution and support flexible business models such as try-before-buy, on-demand reading, superdistribution, etc.

关键词： CEBX fixed layout content reflow document linearization segment-based document protection

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Three-domain Image Representation for Personal Photo Album Management

Three-domain Image Representation for Personal Photo Album M...

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conference on Imaging and Printing in a Web 2.0 World;and multimedia content access - algorithms and systems IV

作者： Ardizzone, E. La Cascia, M. Morana, M. Vella, F. Univ Palermo Dipartimento Ingn Informat Viale Sci Ed 6 Palermo Italy Consiglio Nazl Rice Ist Calcolo & Reti Alte Prestaz Palermo Italy

ISBN: (纸本)9780819479334

In this paper we present a novel approach for personal photo album management. Pictures are analyzed and described in three representation spaces, namely, faces, background and time of capture. Faces are automatically detected and rectified using a probabilistic feature extraction technique. Face representation is then produced by computing PCA (Principal Component Analysis). Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter bank. Temporal data is obtained through the extraction of EXIF (Exchangeable image file format) data. Each image in the collection is then automatically organized using a mean-shift clustering technique. While many systems manage faces and typically allow queries about them we use a common approach to manage multiple aspects, that is, queries regarding people, time and background are dealt with in a homogenous way. We report experimental results on a realistic set, i.e., a personal photo album, of about 2000 images where automatic detection and rectification of faces lead to approximately 800 faces. Significance of clustering has been evaluated and results are very interesting.

关键词： CBIR - content Based Image Retrieval automatic image annotation personal photo album management

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New Performance Evaluation Models for Character Detection in Images

New Performance Evaluation Models for Character Detection in...

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conference on Imaging and Printing in a Web 2.0 World;and multimedia content access - algorithms and systems IV

作者： Wang, YanWei Ding, XiaoQing Liu, ChangSong Wang, Kongqiao Tsinghua Univ Dept Elect Engn Tsinghua Natl Lab Informat Sci & Technol State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China Nokia Res Ctr Multimodal & Multimedia User Interact Beijing 100176 Peoples R China

ISBN: (纸本)9780819479334

Detection of characters regions is a meaningful research work for both highlighting region of interest and recognition for further information processing. A lot of researches have been performed on character localization and extraction and this leads to the great needs of performance evaluation scheme to inspect detection algorithms. In this paper, two probability models are established to accomplish evaluation tasks for different applications respectively. For highlighting region of interest, a Gaussian probability model, which simulates the property of a low-pass Gaussian filter of human vision system (HVS), was constructed to allocate different weights to different character parts. It reveals the greatest potential to describe the performance of detectors, especially, when the result detected is an incomplete character, where other methods cannot effectively work. For the recognition destination, we also introduced a weighted probability model to give an appropriate description for the contribution of detection results to final recognition results. The validity of performance evaluation models proposed in this paper are proved by experiments on web images and natural scene images. These models proposed in this paper may also be able to be applied in evaluating algorithms of locating other objects, like face detection and more wide experiments need to be done to examine the assumption.

关键词： performance evaluation character detection probability model

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content-Based Image Retrieval With Ontological Ranking

Content-Based Image Retrieval With Ontological Ranking

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conference on Imaging and Printing in a Web 2.0 World;and multimedia content access - algorithms and systems IV

作者： Tsai, Shen-Fu Tsai, Min-Hsuan Huang, Thomas S. Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA

ISBN: (纸本)9780819479334

Images are a much more powerful medium of expression than text, as the adage says: "One picture is worth a thousand words." It is because compared with text consisting of an array of words, an image has more degrees of freedom and therefore a more complicated structure. However, the less limited structure of images presents researchers in the computer vision community a tough task of teaching machines to understand and organize images, especially when a limit number of learning examples and background knowledge are given. The advance of internet and web technology in the past decade has changed the way human gain knowledge. People, hence, can exchange knowledge with others by discussing and contributing information on the web. As a result, the web pages in the internet have become a living and growing source of information. One is therefore tempted to wonder whether machines can learn from the web knowledge base as well. Indeed, it is possible to make computer learn from the internet and provide human with more meaningful knowledge. In this work, we explore this novel possibility on image understanding applied to semantic image search. We exploit web resources to obtain links from images to keywords and a semantic ontology constituting human's general knowledge. The former maps visual content to related text in contrast to the traditional way of associating images with surrounding text;the latter provides relations between concepts for machines to understand to what extent and in what sense an image is close to the image search query. With the aid of these two tools, the resulting image search system is thus content-based and moreover, organized. The returned images are ranked and organized such that semantically similar images are grouped together and given a rank based on the semantic closeness to the input query. The novelty of the system is twofold: first, images are retrieved not only based on text cues but their actual contents as well;second, the grouping is

关键词： Image retrieval ontology multimedia

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Using ePub as framework for the automated collection, tagging, and transformation of web content for cross-media publication

Using ePub as framework for the automated collection, taggin...

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Imaging and Printing in a Web 2.0 World;and multimedia content access: algorithms and systems IV

作者： Henderson, Tona Battle, Steven Bernius, Matt Choudhury, Manu Open Publishing Lab. Rochester Institute of Technology Rochester NY United States HP Labs. United States

In this paper, we describe the development of Page2Pub, a Firefox extension for gathering, unifying, and publishing a wide variety of web based materials. © 2010 Copyright SPIE - The International Society for Opt... 详细信息

ISBN: (纸本)9780819479334

关键词： Semantic Web

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The Task-Dependent Effect of Tags and Ratings on Social Media access

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ACM TRANSACTIONS ON INFORMATION systems 2010年第4期28卷 21.1-21.42页

作者： Clements, Maarten De Vries, Arjen P. Reinders, Marcel J. T. Delft Univ Technol Fac Elect Engn Math & Comp Sci EEMCS NL-2600 AA Delft Netherlands

Recently, online social networks have emerged that allow people to share their multimedia files, retrieve interesting content, and discover like-minded people. These systems often provide the possibility to annotate the content with tags and ratings. Using a random walk through the social annotation graph, we have combined these annotations into a retrieval model that effectively balances the personal preferences and opinions of like-minded users into a single relevance ranking for either content, tags, or people. We use this model to identify the influence of different annotation methods and system design aspects on common ranking tasks in social content systems. Our results show that a combination of rating and tagging information can improve tasks like search and recommendation. The optimal influence of both sources on the ranking is highly dependent on the retrieval task and system design. Results on content search and tag suggestion indicate that the profile created by a user's annotations can be used effectively to adapt the ranking to personal preferences. The random walk reduces sparsity problems by smoothly integrating indirectly related concepts in the relevance ranking, which is especially valuable for cold-start users or individual tagging systems like YouTube and Flickr.

关键词： algorithms Experimentation Human Factors Personalization content retrieval recommendation social media random walk rating tagging librarything movielens

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Intelligent content Retrieval using a Visual Vocabulary and Geometric Constraints

Intelligent Content Retrieval using a Visual Vocabulary and ...

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2010 IEEE World Congress on Computational Intelligence

作者： Spyrou, Evaggelos Kalantidis, Yannis Tolias, Giorgos Mylonas, Phivos Kollias, Stefanos Natl Tech Univ Athens Image Video & Multimedia Syst Lab Sch Elect & Comp Engn GR-15773 Athens Greece

ISBN: (纸本)9781424469208

During the last decades multimedia processing has emerged as an important technology to retrieve content based on similar data. Moreover, recent developments in the fields of high definition (HD) multimedia content and personal content collections (personal camcorders and digital still image cameras) tend to generate a huge volume of multimedia data everyday. Thus, the need for a meaningful, quick organization and access to generated content is now more than necessary;however, it still remains a rather difficult problem to be tackled both by humans and computers. In this paper we propose an intelligent extension of traditional image analysis methodologies towards more efficient digital content retrieval. The main idea is to extend local feature extraction methodologies by introducing additional geometrical constraints in the process. The proposed approach is tested and evaluated on a number of publicly available image datasets and results are very promising.

关键词： content-based retrieval digital content retrieval digital still image cameras feature extraction feature extraction method geometric constraint high definition multimedia content image retrieval intelligent content retrieval multimedia computing multimedia processing personal camcorders personal content collection visual vocabulary vocabulary

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Ubiquitous picture rich content representation

Ubiquitous picture rich content representation

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conference on Imaging and Printing in a Web 2.0 World;and multimedia content access - algorithms and systems IV

作者： Wang, Wiley Dean, Jennifer Muzzolini, Russ Shutterfly Inc. (United States)

ISBN: (纸本)9780819479334

The amount of digital images taken by the average consumer is consistently increasing. People enjoy the convenience of storing and sharing their pictures through online (digital) and offline (traditional) media. A set of pictures can be uploaded to: online photo services, web blogs and social network websites. Alternatively, these images can be used to generate: prints, cards, photo books or other photo products. Through uploading and sharing, images are easily transferred from one format to another. And often, a different set of associated content (text, tags) is created across formats. For example, on his web blog, a user may journal his experiences of his recent travel;on his social network website, his friends tag and comment on the pictures;in his online photo album, some pictures are titled and keyword-tagged. When the user wants to tell a complete story, perhaps in a photo book, he must collect, across all formats: the pictures, writings and comments, etc. and organize them in a book format. The user has to arrange the content of his trip in each format. The arrangement, the associations between the images, tags, keywords and text, cannot be shared with other formats. In this paper, we propose a system that allows the content to be easily created and shared across various digital media formats. We define a uniformed data association structure to connect: images, documents, comments, tags, keywords and other data. This content structure allows the user to switch representation formats without reediting. The framework under each format can emphasize (display or hide) content elements based on preference. For example, a slide show view will emphasize the display of pictures with limited text;a blog view will display highlighted images and journal text;and the photo book will try to fit in all images and text content. In this paper, we will discuss the strategy to associate pictures with text content, so that it can naturally tell a story. We will also list sampl

关键词： photo book photo sharing website content association content representation

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