Limitation and Challenges: Image/Video Search & Retrieval

First MUVIS system has been developed three years ago, supporting image indexing and means to retrieve images from large image databases using image visual and semantic features such as color, texture and shape. Recently, MUVIS project has been reformed to become a PC-based system, which supports indexing, browsing and querying on various multimedia types such as audio, video and image. Furthermore the system allows real-time audio and video capturing, encoding by last generation codecs such as if requested, recording while indexing into a database in such a way that they can be retrieved efficiently. In this paper, we describe the system features with underlying applications and outline the mean philosophy. Query and browsing capabilities of the MUVIS technology will be demonstrated during the conference.

International Journal of Computer Applications, 2012

Retrieval of multimedia has become a requirement for many contemporary information systems. These systems need to provide browsing, querying, navigation, and, sometimes, composition capabilities involving various forms of media. In this survey, we review techniques for text, image, audio and video retrieval. We first look at indexing and retrieval techniques for text, audio, image and video. We also discuss features visual features for video retrieval such as colour, texture, shape. The indexing techniques are discussed for these features. We also compare most popular techniques used for indexing and retrieval.

1990

Current conventional Database Management Systems (DBMS) manage only alphanumeric data. However, data to be stored in the future is expected to include some multimedia form, such as images, graphics, sounds or signals. The structure and the semantics of the media data and the operations on that data are complex. It is not clear what requirements are needed in a DBMS to manage this kind of data. It is also not clear what is needcd in the data model to support this kind of data; nor what the user interface should be for such a system. The goal of the Multimedia Database Management System project in the computer science department of the Naval Post Graduate School is to build into a Database Management System (DBMS) the capability to manage multimedia data, as well as the formatted data, and define operations on multimedia data. This thesis, focusing only on the media data of image and sound, first describes the operations of such a system, then discusses the general design of it, and finally outline the detailed design and implementation of the retrieval operation. 20 Distribution/Availability of Abstract 21 Abstract Security Classification [N unclassified/unlimited 1 same as report [] DTIC users Unclassified "2a Nam-c of Responsilc lndh idual 22b Telephone (Include Area code} 22c Office S. mbol Vincent Y. Lum (408r 646-2693 52Lu DD FORM 1473, 84 MAR 83 APR edition may be used until exhausted security classification of this page All other editions are obsolete Unclassified Approved for public release; distribution is unlimited.

Methods, Standards and Tools, 2005

By the end of the last century the question was not whether digital archives are technically and economically viable, but rather how digital archives would be efficient and informative. In this framework, different scientific fields such as, on the one hand, development of database management systems, and, on the other hand, processing and analysis of multimedia data, as well as artificial and computational intelligence methods, have observed a close cooperation with each other during the past few years. The attempt has been to develop intelligent and efficient human-computer interaction systems, enabling the user to access vast amounts of heterogeneous information, stored in different sites and archives.

IEEE 6th Workshop on Multimedia Signal Processing, 2004.

Multimedia databases are extending the scope of traditional databases to handle the complex structure of multi• media objects. Models for multimedia information must include representations for the structure and content of severa] media in a form that allows flexibility in retrie,'al. Content•based retrienl is the main motivation behind recent research in multimedia databases. The task of searching in video and audio content is made hard by the nature of audiovisual data where, unlike text, there is no direct syntactic channel between the object and its meaning [1]-[3]. We propose a model for multimedia content storage and retrie,'al accounting for both context and content information and taking adl'antage of their dependencies for effective retrieval. We then describe a prototype multimedia database with a retrieval interface. It has been used as a workbench for testing the representation model and integrating tools for feature extraction, information interchange and retriel'al. The workbench allows an easy inclusion of new tools for content analysis and new methods for context• and content-based retrieval while offering storage and access for both the actual digital content and its metadata.

ArXiv, 2012

Content-based multimedia information retrieval is an interesting research area since it allows retrieval based on inherent characteristic of multimedia objects. For example retrieval based on visual characteristics such as colour, shapes or textures of objects in images or retrieval based on spatial relationships among objects in the media (images or video clips). This paper reviews some work done in image and video retrieval and then proposes an integrated model that can handle images and video clips uniformly. Using this model retrieval on images or video clips can be done based on the same framework.

AkiNik Publications, 2025

The exponential growth of multimedia data in diverse fields, including entertainment, education, healthcare, and surveillance, necessitates efficient systems for storing, indexing, and retrieving complex multimedia content. This chapter explores the foundational data structures and algorithms critical for managing multimedia databases effectively. It discusses spatial, temporal, and semantic challenges, emphasizing advanced indexing mechanisms like R-trees, quadtrees, and graph-based representations for scalable and accurate data management. Techniques for content-based retrieval, real-time processing, and adaptive compression are examined in detail, showcasing their applications in content recommendation systems, digital libraries, AR/VR platforms, and surveillance. The integration of artificial intelligence and distributed architectures emerges as a pivotal future direction, enabling semantic understanding, real-time analytics and enhanced scalability. The chapter also highlights challenges, including the semantic gap, computational demands, and bias in AI systems, while proposing innovative solutions such as neural semantic search, edge computing, and immersive multimedia experiences. By bridging theoretical advancements and practical applications, this chapter provides a comprehensive framework for developing intelligent multimedia database systems that are efficient, adaptive, and future-ready.

2003

Abstract MUVIS is a series of CBIR systems. The first one has been developed in late 90s to support indexing and retrieval in large image databases using visual and semantic features such as color, texture and shape. During recent years, MUVIS has been reformed to become a PC-based framework, which supports indexing, browsing and querying of various multimedia types such as audio, video, audio/video interlaced and several image formats.

Journal of Universal Computer Science, 2001

The utilization of new emerging standards such as MPEG-7 is expected to be a major breakthrough for content-based multimedia data retrieval. The main features of the MPEG standards series and of related standards, formats and protocols are presented. It is discussed, how they, despite their partially early and immature stage, can best be utilized to yield effective results in the context of a knowledge management environment. Complementary to that, the current status and state of the art in content-based retrieval for images, video and audio content is briefly presented. In the context of the KNOW-Center we are developing a prototype platform to implement a user friendly and highly informative access to audiovisual content as a potential component for a future knowledge management system. The technical requirements and the system architecture for the prototype platform are described.

Architectural Issues of Web-Enabled Electronic Business, 2000

The objective of this chapter is to introduce the reader to a general architectural framework for a broad array of retrievals of multimedia data required by various applications. This framework contains more than the traditional client/server architecture and even more than the existing three-tier architectures. This chapter introduces the reader to many critical issues involved in multimedia retrieval over the Internet. A new architectural framework is proposed to cover a variety of multimedia applications over the Internet and the World Wide Web. This framework has the three main objectives of (1) proposing a layered architecture to facilitated design and separate different issues, (2) covering a large number of multimedia applications, and finally, (3) making use of existing and well-established technology, such as Mobile Agents, SQL databases, and cache managements schemes. The proposed architectural framework separates issues involved in multimedia retrieval into five layers, namely: keyword searching and data servers, proxy servers, domain and department archives, mobile user agents, and the users. Through these five layers, various customized solutions to a large array of problems will be proposed and applied. The chapter offers, but is not limited to, solutions for different problems that arise in retrieval of multimedia data. A list of important open problems is identified at the end of the chapter.