A unified approach to indexing multimedia on the Web

International Conference on Computer Engineering and Applications (ICCEA) 2011 Proceeding, 2011

In this digital era, the use of digital multimedia information is highly utilized and growing very rapidly due to the development of the Internet. Thus, users demand for more effective content-based multimedia information retrieval system (CBMMIRS). The major challenge in this research area is that a multimedia document comprises more than one type of contents (i.e. text, image, audio). In order to address this challenge, many works have been focusing on the indexing techniques development which can accommodate multiple multimedia object representation or known as object features. However, most of the experiments use only one certain kind of collection, for example a collection of WWW pages, video collections, image collections, and so forth. In this paper, we propose a multidimensional approach which could accommodates semantic indexing of various multimedia contents in different multimedia collections, since the fact is that different multimedia documents may share similar information. The architecture comprises three components: (1) collection manager (which manages multimedia documents repository); (2) indexer (which handles multimedia concept detection and indexing); and (3) query processor (which deals with query and search results). Our hypothesis is that the more complete the document (which indexed in many different feature spaces), the more relevant the document and should be ranked higher in the search results.

ACM Transactions on Multimedia Computing, Communications, and Applications, 2006

Extending beyond the boundaries of science, art, and culture, content-based multimedia information retrieval provides new paradigms and methods for searching through the myriad variety of media all over the world. This survey reviews 100+ recent articles on content-based multimedia information retrieval and discusses their role in current research directions which include browsing and search paradigms, user studies, affective computing, learning, semantic queries, new features and media types, high performance indexing, and evaluation techniques. Based on the current state of the art, we discuss the major challenges for the future.

2009

The demand for efficient systems that facilitate searching in multimedia databases and collections is vastly increasing. Application domains include criminology, musicology, trademark registration, medicine and image or video retrieval on the web. This thesis discusses content-based retrieval techniques that can be applied on these databases. The most important operation to support is query-by-example: retrieve items that are to some extent

Content-Based Multimedia Indexing (CBMI) is the multi-disciplinary field broadly aiming at extracting knowledge from multimedia information and providing fluent access to it. CBMI research proposes to develop methods to model, abstract and organise multimedia data in view of fast, effective and accurate access. CBMI covers all the chain from the data to the user. It encompasses a large variety of challenges from multimedia information capture and representation via content understanding and information fusion to effective information indexing and retrieval. Since the early days, CBMI research has therefore produced a wide range of fundamental and application-oriented contributions and has provided methodological guidelines for progressing in the field. Due to its multi-disciplinary nature, CBMI research has also strongly been impacted by progress in adjunct domains such as machine learning, large-scale information storage and processing, and new modes of user interaction.

2019

With the abundance of multimedia content on the World Wide Web, research and learning of effective feature representation and similarity measures have become crucial. Image searching poses several challenges. Lately, many researchers have been exploring the field. Automatic annotation of images based on digital content processing proves to be an encouraging direction in the field. Content based image retrieval system development is an emerging field. Accuracy of the results of semantic search depends on the understanding of searcher’s purpose, the meaning of conditions imposed in the search query and their mapping in the searchable data space. A visual content semantic search engine is proposed in this paper. The search engine employs digital image features for searching the image database. The presented algorithm produces promising results. The performance of our algorithm is tested on an extensive set of tags and queries resulting in accurate and efficient results.

Computer Networks and ISDN Systems, 1997

Search engines are useful because they allow the user to find information of interest from the WorldWide Web. However, most of the popular search engines today are textual; they do not allow the user to find images from the Web. This paper describes a search engine that integrates text and image search. One or more Web sites can be indexed for both textual and image information, allowing the user to search based on keywords or images or both. Another problem with the current search engines is that they show the results as pages of scrolled list; this is not very user-friendly. Therefore our search engine allows the user to visualize the results in various ways. This paper explains the indexing and searching techniques of the search engine and highlights several features of the querying interface to make the retrieval process more efficient. Examples are used to show the usefulness of the technology.

In this paper, an introduction to Multimedia Information Retrieval (MIR) Systems is presented with justifications to their current widespread use. Explanations of the fundamental differences between MIR systems and standard text-based retrieval ones are also provided with highlights on the inadequacy of the use of keyword-based search techniques as the only modality in searching these archives. Several challenges facing MIR systems are expounded with the focus on bridging the semantic gap between human perception and the low-level features used by automated MIR systems to index multimedia data. The paper presents some of the promising future trends and discusses briefly areas that need further investigations.

Proceedings of the Indian Conference on …, 2002

Most web pages typically contain both images and text. However, most current search engines index documents based on text only. In order to facilitate effective search for images on the web, we need to complement text with the visual content of the images. We often look for images containing specific objects having some particular spatial and topological relations among them. In this paper, we describe a system which enables the user to effectively search for images using the image content information including color, component objects and their relations in addition to associated text.

… Challenge of Image Retrieval, University of …, 1998

While pages on the Web contain more and more multimedia information, such as images, videos and audio, today search engines are mostly based on textual information. There is an emerging need of a new generation of search engines that try to exploit the full ...