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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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Overview of multimedia content protection in consumer electronics devices

Overview of multimedia content protection in consumer electr...

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Security and Watermarking of multimedia contents ii

作者： Eskicioglu, Ahmet M. Delp, Edward J. Thomson Consumer Electronics Indianapolis United States

A digital home network is a cluster of digital audio/visual (AN) devices including set-top boxes, TVs, VCRs, DVD players, and general-purpose computing devices such as personal computers. The network may receive copyrighted digital multimedia content from a number of sources. This content may be broadcast via satellite or terrestrial systems, transmitted by cable operators, or made available as prepackaged media (e.g., a digital tape or a digital video disc). Before releasing their content for distribution, the content owners may require protection by specifying access conditions. Once the content is delivered to the consumer, it moves across home the network until it reaches its destination where it is stored or displayed. A copy protection system is needed to prevent unauthorized access to bit streams in transmission from one A/V device to another or while it is in storage on magnetic or optical media. Recently, two fundamental groups of technologies, encryption and watermarking, have been identified for protecting copyrighted digital multimedia content. This paper is an overview of the work done for protecting content owners' investment in intellectual property.

关键词： multimedia systems

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ImageSeeker: A content-based image retrieval system

ImageSeeker: A content-based image retrieval system

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multimedia content access: algorithms and systems iiI

作者： Tawfik, Alaa Fouad, HebatAllah Megahed, Reem Mohamed, Samar Hemayed, Elsayed Computer Engineering Dept. Faculty of Engineering Cairo University Giza Egypt

In many areas of commerce, government, academia, and medicine, large collections of digital images are being used. Usually, the only way of searching these collections is by their name, or by browsing which is unpractical for large number of images. ImageSeeker aims at providing an improved technique to enhance image searching. It focuses on extracting visual contents from images and annotating them;it is based on the concept of CBIR (content Based Image Retrieval) to retrieve the contents of the image based on what it has learnt during past trainings. When a user requests an image for a certain object, all images containing the same object will show up. ImageSeeker maintains high accuracy in finding matching results to the user's query. The system was tested on images containing natural scenes, specifically, see, sand, grass, clouds and sky. © 2009 SPIE-IS&T.

关键词： Search engines

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Subjective evaluation of mobile 3D video content: depth range versus compression artifacts

Subjective evaluation of mobile 3D video content: depth rang...

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Conference on multimedia on Mobile Devices and multimedia content access - algorithms and systems V

作者： Jumisko-Pyykko, Satu Haustola, Tomi Boev, Atanas Gotchev, Atanas Tampere Univ Technol Unit Human Centered Technol POB 589 FI-33101 Tampere Finland Tampere Univ Technol Dept Signal Proc FI-33101 Tampere Finland

ISBN: (纸本)9780819484185

Mobile 3D television is a new form of media experience, which combines the freedom of mobility with the greater realism of presenting visual scenes in 3D. Achieving this combination is a challenging task as greater viewing experience has to be achieved with the limited resources of the mobile delivery channel such as limited bandwidth and power constrained handheld player. This challenge sets need for tight optimization of the overall mobile 3DTV system. Presence of depth and compression artifacts in the played 3D video are two major factors that influence viewer's subjective quality of experience and satisfaction. The primary goal of this study has been to examine the influence of varying depth and compression artifacts on the subjective quality of experience for mobile 3D video content. In addition, the influence of the studied variables on simulator sickness symptoms has been studied and vocabulary-based descriptive quality of experience has been conducted for a sub-set of variables in order to understand the perceptual characteristics in detail. In the experiment, 30 participants have evaluated the overall quality of different 3D video contents with varying depth ranges and compressed with varying quantization parameters. The test video content has been presented on a portable autostereoscopic LCD display with horizontal double density pixel arrangement. The results of the psychometric study indicate that compression artifacts are a dominant factor determining the quality of experience compared to varying depth range. More specifically, contents with strong compression has been rejected by the viewers and deemed unacceptable. The results of descriptive study confirm the dominance of visible spatial artifacts along the added value of depth for artifact-free content. The level of visual discomfort has been determined as not offending.

关键词： mobile 3D television subjective evaluation quality of experience quality perception

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ACO-based media content adaptation for e-learning environments

ACO-based media content adaptation for e-learning environmen...

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2014 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement systems and Applications, CIVEMSA 2014

作者： Shamim Hossain, M. Masud, Mehedi Alelaiwi, Abdulhameed A. Alghamdhi, Abdullah Software Engineering Dept. CCIS King Saud University Riyadh 11451 Saudi Arabia Computer Science Dept. Taif University Saudi Arabia

ISBN: (纸本)9781479926138

The advances of ubiquitous communication infrastructures, the rapid adoption of mobile devices and pervasive computing technologies has allowed e-learning users access to multimedia learning contents in e-learning environments. However, because of the diversity and heterogeneity of the mobile users, their preferences, and the rich multimedia learning content, it is a major challenge for the access of learning content by the desired devices in the e- learning environment to user's satisfaction in terms of QoS demands. In order to alleviate the challenge of learning content mismatch, content adaptation is essential. To this end, we propose an ACO-based multimedia content adaptation approach, which inherits the adoption of ACO-based path selection behavior in the path computation for appropriate learning content customization. We compare our proposed approach with other two competitive algorithms, measure the performance and find that our proposed algorithms outperforms the basic AntNet and Genetic in terms of success rate, latency, runtime comparison and convergence. The performance evaluations are conducted using NetLogo simulation environment. © 2014 IEEE.

关键词： Computer aided instruction

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Material Classification and Automatic content Enrichment of Images Using Supervised Learning and Knowledge Bases

Material Classification and Automatic Content Enrichment of ...

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Conference on multimedia on Mobile Devices and multimedia content access - algorithms and systems V

作者： Mallepudi, Sri Abhishikth Calix, Ricardo A. Knapp, Gerald M. Louisiana State Univ Baton Rouge LA 70803 USA

ISBN: (纸本)9780819484185

In recent years there has been a rapid increase in the size of video and image databases. Effective searching and retrieving of images from these databases is a significant current research area. In particular, there is a growing interest in query capabilities based on semantic image features such as objects, locations, and materials, known as content-based image retrieval. This study investigated mechanisms for identifying materials present in an image. These capabilities provide additional information impacting conditional probabilities about images (e. g. objects made of steel are more likely to be buildings). These capabilities are useful in Building Information Modeling (BIM) and in automatic enrichment of images. I2T methodologies are a way to enrich an image by generating text descriptions based on image analysis. In this work, a learning model is trained to detect certain materials in images. To train the model, an image dataset was constructed containing single material images of bricks, cloth, grass, sand, stones, and wood. For generalization purposes, an additional set of 50 images containing multiple materials (some not used in training) was constructed. Two different supervised learning classification models were investigated: a single multi-class SVM classifier, and multiple binary SVM classifiers (one per material). Image features included Gabor filter parameters for texture, and color histogram data for RGB components. All classification accuracy scores using the SVM-based method were above 85%. The second model helped in gathering more information from the images since it assigned multiple classes to the images. A framework for the I2T methodology is presented.

关键词： Image classification Binary data RGB color model Machine learning Image filtering Data modeling Feature extraction Databases Buildings content based image retrieval

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Flexible user interface for efficient content-based video surveillance retrieval: Design and evaluation

Flexible user interface for efficient content-based video su...

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multimedia content access: algorithms and systems iiI

作者： Meessen, Jerome Coterot, Mathieu De Vleeschouwer, Christophe Desurmont, Xavier Macq, Benoit Multitel B-7000 Mons Belgium Université Catholique de Louvain Communication and Remote Sensing Lab. Louvain-la-Neuve Belgium

The major drawback of interactive retrieval systems is the potential frustration of the user that is caused by an excessive labelling work. Active learning has proven to help solving this issue, by carefully selecting the examples to present to the user. In this context, the design of the user interface plays a critical role since it should invite the user to label the examples elected by the active learning. This paper presents the design and evaluation of an innovative user interface for image retrieval. It has been validate using real-life IEEE PETS video surveillance data. In particular, we investigated the most appropriate repartition of the display area between the retrieved video frames and the active learning examples, taking both objective and subjective user satisfaction parameters into account. The flexibility of the interface relies on a scalable representation of the video content such as Motion JPEG 2000 in our implementation. © 2009 SPIE-IS&T.

关键词： User interfaces

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Efficient video file allocation schemes for video-on-demand services

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multimedia systems 1997年第5期5卷 283-296页

作者： Wang, YW Liu, JCL Du, DHC Hsieh, JW UNIV MINNESOTA DISTRIBUTED MULTIMEDIA RES CTRMINNEAPOLISMN 55455 UNIV MINNESOTA DEPT COMP SCIMINNEAPOLISMN 55455

A video-on-demand (VOD) server needs to store hundreds of movie titles and to support thousands of concurrent accesses. This, technically and economically, imposes a great challenge on the design of the disk storage subsystem of a VOD server. Due to different demands for different movie titles, the numbers of concurrent accesses to each movie can differ a lot. We define access profile as the number of concurrent accesses to each movie title that should be supported by a VOD server. The access profile is derived based on the popularity of each movie title and thus serves as a major design goal for the disk storage subsystem. Since some popular (hot) movie titles may be concurrently accessed by hundreds of users and a current high-end magnetic disk array (disk) can only support tens of concurrent accesses, it is necessary to replicate and/or stripe the hot movie files over multiple disk arrays. The consequence of replication and striping of hot movie titles is the potential increase on the required number of disk arrays. Therefore, how to replicate, stripe, and place the movie files over a minimum number of magnetic disk arrays such that a given access profile can be supported is an important problem. In this paper, we formulate the problem of the video file allocation over disk arrays, demonstrate that it is a NP-hard problem, and present some heuristic algorithms to find the near-optimal solutions. The result of this study can be applied to the design of the storage subsystem of a VOD server to economically minimize the cost or to maximize the utilization of disk arrays.

关键词： multimedia video-on-demand concurrent access MPEG-ii RAID-3 replication striping 2D vector packing

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Deep Learning-Based Detection of Inappropriate Speech content for Film Censorship

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IEEE access 2022年 10卷 101697-101715页

作者： Wazir, Abdulaziz Saleh Ba Karim, Hezerul Abdul Lyn, Hor Sui Fauzi, Mohammad Faizal Ahmad Mansor, Sarina Lye, Mohd Haris Multimedia Univ Fac Engn Cyberjaya 63000 Malaysia

Audible content has become an effective tool for shaping one's personality and character due to the ease of accessibility to a huge audible content that could be an independent audio files or an audio of online videos, movies, and television programs. There is a huge necessity to filter inappropriate audible content of the easily accessible videos and films that are likely to contain an inappropriate speech content. With this in view, all the broadcasting and online video/audio platform companies hire a lot of manpower to detect the foul voices prior to censorship. The process has a large cost in terms of manpower, time and financial resources. In addition to inaccurate detection of foul voices due to fatigue of manpower and weakness of human visual and hearing system in long time and monotonous tasks. As such, this paper proposes an intelligent deep learning-based system for film censorship through a fast and accurate detection and localization approach using advanced deep Convolutional Neural Networks (CNNs). The dataset of foul language containing isolated words samples and continuous speech were collected, annotated, processed, and analyzed for the development of automated detection of inappropriate speech content. The results indicated the feasibility of the suggested systems by reporting a high volume of inappropriate spoken terms detection. The proposed system outperformed state-of-the-art baseline algorithms on the novel foul language dataset evaluation metrics in terms of macro average AUC (93.85%), weighted average AUC (94.58%), and all other metrics such as F1-score. Additionally, proposed acoustic system outperformed ASR-based system for profanity detection based on the evaluation metrics including AUC, accuracy, precision, and F1-score. Additionally, proposed system was proven to be faster than human manual screening and detection of audible content for films' censorship.

关键词： Speech recognition Acoustics Computational modeling Deep learning Motion pictures Censorship Speech processing Foul language speech recognition key word spotting spoken term detection censorship deep learning convolutional neural network

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Data mining learning bootstrap through semantic thumbnail analysis

Data mining learning bootstrap through semantic thumbnail an...

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Conference on multimedia content access - algorithms and systems

作者： Battiato, Sebastiano Farinella, Giovanni Maria Giuffrida, Giovanni Tribulato, Giuseppe Univ Catania Dipartimento Matemat & Informat Viale Andrea Doria6 I-95125 Catania Italy

ISBN: (纸本)9780819466198

The rapid increase of technological innovations in the mobile phone industry induces the research community to develop new and advanced systems to optimize services offered by mobile phones operators (telcos) to maximize their effectiveness and improve their business. Data mining algorithms can run over data produced by mobile phones usage (e.g. image, video, text and logs files) to discover user's preferences and predict the most likely (to be purchased) offer for each individual customer. One of the main challenges is the reduction of the learning time and cost of these automatic tasks. In this paper we discuss an experiment where a commercial offer is composed by a small picture augmented with a short text describing the offer itself. Each customer's purchase is properly logged with all relevant information. Upon arrival of new items we need to learn who the best customers (prospects) for each item are, that is, the ones most likely to be interested in purchasing that specific item. Such learning activity is time consuming and, in our specific case, is not applicable given the large number of new items arriving every day. Basically, given the current customer base we are not able to learn on all new items. Thus, we need somehow to select among those new items to identify the best candidates. We do so by using a joint analysis between visual features and text to estimate how good each new item could be, that is, whether or not is worth to learn on it. Preliminary results show the effectiveness of the proposed approach to improve classical data mining techniques.

关键词： semantic image analysis data mining content based image retrieval learning bootstrap

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