Página 1 dos resultados de 79 itens digitais encontrados em 0.002 segundos

Alinhamento de metadados da indústria de broadcast multimidia no contexto da TV digital com a web semântica; Alignment of broadcast multimedia industry metadata in the context of digital tv with the semantic web

Rodrigo Cascão Araújo
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Formato: application/pdf
PT
Relevância na Pesquisa
36.42%
A integração da Internet e das tecnologias de comunicação móveis com as plataformas de televisão têm provido aos telespectadores novos serviços interativos de conteúdo digital. Devido a estes fatores, os equipamentos para o consumidor têm se tornado cada vez mais sofisticados, suportando uma variedade de conteúdos e conectividade com outras redes e dispositivos. A TV digital é uma plataforma híbrida que combina elementos da televisão tradicional com a Internet, provendo ao usuário o acesso a uma diversidade de conteúdos de mídia interativa. Com o crescimento do volume e da diversidade de serviços e conteúdos multimídia, a televisão está enfrentando os mesmos desafios de complexidade e excesso de informações que já vinham sendo encarados por outras mídias digitais relacionadas com a Internet. A tecnologia de metadados pode ser uma alternativa para lidar com esta complexidade de serviços e conteúdos digitais de forma prática e eficiente. Metadados são dados que complementam as informações digitais dos conteúdos multimídia com o objetivo de descrevê-los de forma sintática e semântica, facilitando a estruturação e o gerenciamento de grandes volumes de informação. O uso de metadados em TV digital não se restringe a construção de um ferramental de busca e indexação de conteúdos multimídia...

A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Chetterjee, Kasturi
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
36.38%
Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric data, will be inefficient. ^ An index structure is the backbone of any database management system. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, in this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally...

A Scalable Multimedia Content Processing Framework with Application to TV Shopping

Fleites, Fausto C
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Relevância na Pesquisa
36.32%
The advent of smart TVs has reshaped the TV-consumer interaction by combining TVs with mobile-like applications and access to the Internet. However, consumers are still unable to seamlessly interact with the contents being streamed. An example of such limitation is TV shopping, in which a consumer makes a purchase of a product or item displayed in the current TV show. Currently, consumers can only stop the current show and attempt to find a similar item in the Web or an actual store. It would be more convenient if the consumer could interact with the TV to purchase interesting items. Towards the realization of TV shopping, this dissertation proposes a scalable multimedia content processing framework. Two main challenges in TV shopping are addressed: the efficient detection of products in the content stream, and the retrieval of similar products given a consumer-selected product. The proposed framework consists of three components. The first component performs computational and temporal aware multimedia abstraction to select a reduced number of frames that summarize the important information in the video stream. By both reducing the number of frames and taking into account the computational cost of the subsequent detection phase, this component component allows the efficient detection of products in the stream. The second component realizes the detection phase. It executes scalable product detection using multi-cue optimization. Additional information cues are formulated into an optimization problem that allows the detection of complex products...

Aplicación del modelo Bag-of-Words al reconocimiento de imágenes

Pardo Feijoo, Sara
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/bachelorThesis; info:eu-repo/semantics/masterThesis Formato: application/pdf
SPA
Relevância na Pesquisa
46.56%
Object recognition on images has been more investigated in the recent years. Its principal application is the image retrieval and, therefore, image searchers would find the solution to the query based on whether the image has certain objects in its visual content or not instead of based on the adjacent textual annotations. Content based image retrieval would improve notoriously the quality of searchers. It is neccesary to have models that classify an image based on its low level features. In this project, it is used the ‘Bag of words’ model. Multimedia information retrieval entails many fields involved, and has many applications. The objective of this project is the indexing of images of a database based on content. It tries to eliminate the semantic gap finding the descriptors of each imagen, and therefore decide to which class or which semantic concept belongs.--------------------------------------------------------------------; El reconocimiento de objetos en imágenes es un campo cada vez más investigado y que se aplica principalmente a la recuperación de imágenes basada en contenido, es decir, a buscadores de imágenes que encontrarán la solución a una consulta basándose en si la imagen contiene ciertos objetos o no en función de su contenido visual...

A multimedia indexing and retrieval framework for multimedia database systems

Zhang, Chengcui
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
36.75%
The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval...

Multi-Concept Learning With Large-Scale Multimedia Lexicons

Xie, Lexing; Yan, Rong; Yang, Jun
Fonte: I.K. International Publishing House Pvt Ltd Publicador: I.K. International Publishing House Pvt Ltd
Tipo: Conference paper
Relevância na Pesquisa
36.3%
Multi-concept learning is an important problem in multimedia content analysis and retrieval. It connects two key components in the multimedia semantic ecosystem: multimedia lexicon and semantic concept detection. This paper aims to answer two questions re

Labeling and Retrieval of Emotionally-Annotated Images using WordNet

Horvat, Marko; Grbin, Anton; Gledec, Gordan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.3%
Repositories of images with semantic and emotion content descriptions are valuable tools in many areas such as Affective Computing and Human-Computer Interaction, but they are also important in the development of multimodal searchable online databases. Ever growing number of image documents available on the Internet continuously motivates research of better annotation models and more efficient retrieval methods which use mash-up of available data on semantics, scenes, objects, events, context and emotion. Formal knowledge representation of such high-level semantics requires rich, explicit, human but also machine-processable information. To achieve these goals we present an online ontology-based image annotation tool WNtags and demonstrate its usefulness in knowledge representation and image retrieval using the International Affective Picture System database. The WNtags uses WordNet as image tagging glossary but considers Suggested Upper Merged Ontology as the preferred upper labeling formalism. The retrieval is performed using node distance metrics to establish semantic relatedness between a query and the collaboratively weighted tags describing high-level image semantics, after which the result is ranked according to the derived importance. We also elaborate plans to improve the WNtags to create a collaborative Web-based multimedia repository for research in human emotion and attention.; Comment: 16 pages...

Retrieval of multimedia stimuli with semantic and emotional cues: Suggestions from a controlled study

Horvat, Marko; Kukolja, Davor; Ivanec, Dragutin
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 27/05/2015
Relevância na Pesquisa
36.61%
The ability to efficiently search pictures with annotated semantics and emotion is an important problem for Human-Computer Interaction with considerable interdisciplinary significance. Accuracy and speed of the multimedia retrieval process depends on the chosen metadata annotation model. The quality of such multifaceted retrieval is opposed to the potential complexity of data setup procedures and development of multimedia annotations. Additionally, a recent study has shown that databases of emotionally annotated multimedia are still being predominately searched manually which highlights the need to study this retrieval modality. To this regard we present a study with N = 75 participants aimed to evaluate the influence of keywords and dimensional emotions in manual retrieval of pictures. The study showed that if the multimedia database is comparatively small emotional annotations are sufficient to achieve a fast retrieval despite comparatively lesser overall accuracy. In a larger dataset semantic annotations became necessary for efficient retrieval although they contributed to a slower beginning of the search process. The experiment was performed in a controlled environment with a team of psychology experts. The results were statistically consistent with validates measures of the participants' perceptual speed.; Comment: 4 pages...

WNtags: A Web-Based Tool For Image Labeling And Retrieval With Lexical Ontologies

Horvat, Marko; Grbin, Anton; Gledec, Gordan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 09/02/2013
Relevância na Pesquisa
36.29%
Ever growing number of image documents available on the Internet continuously motivates research in better annotation models and more efficient retrieval methods. Formal knowledge representation of objects and events in pictures, their interaction as well as context complexity becomes no longer an option for a quality image repository, but a necessity. We present an ontology-based online image annotation tool WNtags and demonstrate its usefulness in several typical multimedia retrieval tasks using International Affective Picture System emotionally annotated image database. WNtags is built around WordNet lexical ontology but considers Suggested Upper Merged Ontology as the preferred labeling formalism. WNtags uses sets of weighted WordNet synsets as high-level image semantic descriptors and query matching is performed with word stemming and node distance metrics. We also elaborate our near future plans to expand image content description with induced affect as in stimuli for research of human emotion and attention.; Comment: 10 pages, 3 figures, published in 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 10-12 Sep 2012, San Sebastian, Spain

Learning Contextualized Semantics from Co-occurring Terms via a Siamese Architecture

Sandouk, Ubai; Chen, Ke
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 17/06/2015
Relevância na Pesquisa
36.28%
One of the biggest challenges in Multimedia information retrieval and understanding is to bridge the semantic gap by properly modeling concept semantics in context. The presence of out of vocabulary (OOV) concepts exacerbates this difficulty. To address the semantic gap issues, we formulate a problem on learning contextualized semantics from descriptive terms and propose a novel Siamese architecture to model the contextualized semantics from descriptive terms. By means of pattern aggregation and probabilistic topic models, our Siamese architecture captures contextualized semantics from the co-occurring descriptive terms via unsupervised learning, which leads to a concept embedding space of the terms in context. Furthermore, the co-occurring OOV concepts can be easily represented in the learnt concept embedding space. The main properties of the concept embedding space are demonstrated via visualization. Using various settings in semantic priming, we have carried out a thorough evaluation by comparing our approach to a number of state-of-the-art methods on six annotation corpora in different domains, i.e., MagTag5K, CAL500 and Million Song Dataset in the music domain as well as Corel5K, LabelMe and SUNDatabase in the image domain. Experimental results on semantic priming suggest that our approach outperforms those state-of-the-art methods considerably in various aspects.

Multimedia stimuli databases usage patterns: a survey report

Horvat, Marko; Popović, Siniša; Ćosić, Krešimir
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.37%
Multimedia documents such as images, sounds or videos can be used to elicit emotional responses in exposed human subjects. These stimuli are stored in affective multimedia databases and successfully used for a wide variety of research in affective computing, human-computer interaction and cognitive sciences. Affective multimedia databases are simple repositories of multimedia documents with annotated high-level semantics and affective content. Although important all affective multimedia databases have numerous deficiencies which impair their applicability. To establish a better understanding of how experts use affective multimedia databases an online survey was conducted into the subject. The survey results are statistically significant and indicate that contemporary databases lack stimuli with rich semantic and emotional content. 73.33% of survey participants find the databases lacking at least some important semantic or emotion content. Most of the participants consider stimuli descriptions to be inadequate. Overall, 1-2h or more than 24h are generally needed to construct a single stimulation sequence. Almost 84% of the survey participants would like to use real-life videos in their research. Experts unequivocally recognize the need for an intelligent stimuli retrieval application that would assist them in experimentation. Almost all experts agree such applications could be useful in their work.; Comment: 5 pages...

Unsupervised Visual and Textual Information Fusion in Multimedia Retrieval - A Graph-based Point of View

Csurka, Gabriela; Ah-Pine, Julien; Clinchant, Stéphane
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 27/01/2014
Relevância na Pesquisa
46.5%
Multimedia collections are more than ever growing in size and diversity. Effective multimedia retrieval systems are thus critical to access these datasets from the end-user perspective and in a scalable way. We are interested in repositories of image/text multimedia objects and we study multimodal information fusion techniques in the context of content based multimedia information retrieval. We focus on graph based methods which have proven to provide state-of-the-art performances. We particularly examine two of such methods : cross-media similarities and random walk based scores. From a theoretical viewpoint, we propose a unifying graph based framework which encompasses the two aforementioned approaches. Our proposal allows us to highlight the core features one should consider when using a graph based technique for the combination of visual and textual information. We compare cross-media and random walk based results using three different real-world datasets. From a practical standpoint, our extended empirical analysis allow us to provide insights and guidelines about the use of graph based methods for multimodal information fusion in content based multimedia information retrieval.; Comment: An extended version of the paper: Visual and Textual Information Fusion in Multimedia Retrieval using Semantic Filtering and Graph based Methods...

Semantic Annotation and Search for Educational Resources Supporting Distance Learning

Nithya, C.; Saravanan, K.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 01/03/2014
Relevância na Pesquisa
36.32%
Multimedia educational resources play an important role in education, particularly for distance learning environments. With the rapid growth of the multimedia web, large numbers of education articles video resources are increasingly being created by several different organizations. It is crucial to explore, share, reuse, and link these educational resources for better e-learning experiences. Most of the video resources are currently annotated in an isolated way, which means that they lack semantic connections. Thus, providing the facilities for annotating these video resources is highly demanded. These facilities create the semantic connections among video resources and allow their metadata to be understood globally. Adopting Linked Data technology, this paper introduces a video annotation and browser platform with two online tools: Notitia and Sansu-Wolke. Notitia enables users to semantically annotate video resources using vocabularies defined in the Linked Data cloud. Sansu-Wolke allows users to browse semantically linked educational video resources with enhanced web information from different online resources. In the prototype development, the platform uses existing video resources for education articles. The result of the initial development demonstrates the benefits of applying Linked Data technology in the aspects of reusability...

Semantic-Sensitive Web Information Retrieval Model for HTML Documents

Bassil, Youssef; Semaan, Paul
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 01/04/2012
Relevância na Pesquisa
36.38%
With the advent of the Internet, a new era of digital information exchange has begun. Currently, the Internet encompasses more than five billion online sites and this number is exponentially increasing every day. Fundamentally, Information Retrieval (IR) is the science and practice of storing documents and retrieving information from within these documents. Mathematically, IR systems are at the core based on a feature vector model coupled with a term weighting scheme that weights terms in a document according to their significance with respect to the context in which they appear. Practically, Vector Space Model (VSM), Term Frequency (TF), and Inverse Term Frequency (IDF) are among other long-established techniques employed in mainstream IR systems. However, present IR models only target generic-type text documents, in that, they do not consider specific formats of files such as HTML web documents. This paper proposes a new semantic-sensitive web information retrieval model for HTML documents. It consists of a vector model called SWVM and a weighting scheme called BTF-IDF, particularly designed to support the indexing and retrieval of HTML web documents. The chief advantage of the proposed model is that it assigns extra weights for terms that appear in certain pre-specified HTML tags that are correlated to the semantics of the document. Additionally...

Legal multimedia management and semantic annotation for improved search and retrieval

González-Conejero, Jorge; Teodoro, Emma; Galera, Núria
Fonte: Florence European Press Academic Publishing Publicador: Florence European Press Academic Publishing
Tipo: Parte de Livro Formato: application/pdf
Publicado em //2010; 2010 ENG
Relevância na Pesquisa
46.62%
In this work, we study the possibilities of multimedia management and automatic annotation focused on legal domain. In this field,professionals are used to consume the most part of their time searching and retrieving legal information. For instance, in scenarios as e-discovery and e-learning search and retrieval of the multimedia contents are the basis of the whole applications. In addition, the legal multimedia explosion increases the need of Store these files in a structured form to facilitate the access to this information in an efficient and effective way. Furthermore, the improvements achieved by sensors and video recorders in the last years increase the size of these files, producing an enormous demand of storage capability.JPEG2000 and MPEG-7 are international standards by the ISO/IEC organization that allow to reduce, in some degrees, the amount of data needed to store these files. These standards also permit to include the semantic annotation in the considered file formats, and to access to this information without the need to decompress the contained vídeo or image. How to obtain the semantic information from multimèdia is also studied as well as the different techniques to exploit and combine this information.

The e-Sentencias prototype: a procedural ontology for legal multimedia applications in the Spanish Civil Courts

Casanovas, Pompeu; Binefa i Valls, Xavier; Gracia, Ciro; Teodoro, Emma; Galera, Núria; Blázquez, Mercedes; Poblet, Marta; Carrabina, Jordi; Montón i Macián, Màrius; Montero, Carlos; Serrano, Javier; López-Cobo, José Manuel
Fonte: Amsterdam IOS Press Publicador: Amsterdam IOS Press
Tipo: Parte de Livro Formato: application/pdf
Publicado em //2009; 2009 ENG
Relevância na Pesquisa
36.34%
Search, retrieval, and management of multimedia contents are challenging tasks for users and researchers alike. We introduce a software-hardware system for the global management of the multimedia contents produced by Spanish Civil Courts. The ultimate goal is to obtain an automatic classification of images and segments of the audiovisual records that, coupled with textual semantics, allows an efficient navigation and retrieval of judicial documents and additional legal sources. This paper describes our knowledge acquisition process, sets a typology of Spanish Civil hearings as performed in practice, and a preliminary procedural ontology at its actual stage of development (e-Sentencias ontology). A discussion on procedural, contextual and multimedia ontologies is also provided.

BioMeRSA: The Biology media repository with semantic augmentation

Cornwell, Adam
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
EN_US
Relevância na Pesquisa
36.43%
With computers now capable of easily handling all kinds of multimedia files in vast quantity, and with the Internet now well-suited to exchange these files, we are faced with the challenge of organizing this data in such a way so as to make the information most useful and accessible. This holds true as well for media pertaining to the field of biology, where multimedia is particularly useful in education, as well as in research. To help address this, a software system with a Web-based interface has been developed for improving the accuracy and specificity of multimedia searching and browsing by integrating semantic data pertaining to the field of biology from the Unified Medical Language System (UMLS). Using the Biology Media Repository with Semantic Augmentation (BioMeRSA) system, users who are considered to be `experts' can associate concepts from UMLS with multimedia files submitted by other users to provide semantic context for the files. These annotations are used to retrieve relevant files in the searching and browsing interfaces. A wide variety of image files are currently supported, with some limited support for video and audio files.

Enhancing e-business on the semantic web through automatic multimedia representation

Rege, Manjeet; Dong, Ming; Fotouhi, Farshad
Fonte: IGI Global: Semantic Web Technologies and E-Business Publicador: IGI Global: Semantic Web Technologies and E-Business
Tipo: Parte de Livro
EN_US
Relevância na Pesquisa
46.65%
With the evolution of the next generation Web – the Semantic Web, e-business can be expected to grow into a more collaborative effort in which businesses compete with each other by collaborating to provide the best product to a customer. Electronic collaboration involves data interchange with multimedia data being one of them. Digital multimedia data in various formats has increased tremendously in recent years on the Internet. An automated process that can represent multimedia data in a meaningful way for the Semantic Web is highly desired. In this chapter, we propose an Automatic Multimedia Representation System for the Semantic Web. The proposed system learns a statistical model based on the domain specific training data and performs automatic semantic annotation of multimedia data using XML techniques. We demonstrate the advantage of annotating multimedia data using XML over the traditional keyword based approaches and discuss how it can help e-business.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Yang, Yimin
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: text Formato: application/pdf
Relevância na Pesquisa
66.67%
Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e....

Semantic Cohesion for Image Annotation and Retrieval

Escalante,Hugo Jair; Sucar,Luis Enrique; Montes-y-Gómez,Manuel
Fonte: Centro de Investigación en computación, IPN Publicador: Centro de Investigación en computación, IPN
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/03/2012 EN
Relevância na Pesquisa
46.34%
We present methods for image annotation and retrieval based on semantic cohesion among terms. On the one hand, we propose a region labeling technique that assigns an image the label that maximizes an estimate of semantic cohesion among candidate labels associated to regions in segmented images. On the other hand, we propose document representation techniques based on semantic cohesion among multimodal terms that compose images. We report experimental results that show the effectiveness of the proposed techniques. Additionally, we describe an extension of a benchmark collection for evaluation of the proposed techniques.