Experiments in indexing multimedia data at multiple levels.

The increasing availability of digital images, video, and audio has created exciting new research challenges on the organization of multimedia data for a variety of purposes. While some of these challenges relate to computational techniques (e.g., automatic extraction of visual features for automatic indexing of visual data), others are conceptual in nature (e.g., design of templates for manual indexing of visual data). The key issues are what to index from the data, how to perform the indexing of the data, and how to organize the indices obtained. The indices used to describe content as well as the organization of those indices have a tremendous impact on applications, particularly on large digital libraries where different types of media need to be stored and accessed. Relevant efforts in this direction include the emerging MPEG-7 standard [5], which aims at standardizing tools for describing multimedia data

Image mining: issues, frameworks and techniques

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. Despite the development of many applications and algorithms in the individual research fields cited above, research in image mining is still in its infancy. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining at the end of this paper

Image mining: trends and developments

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

An information-driven framework for image mining

[Abstract]: Image mining systems that can automatically extract semantically meaningful information (knowledge) from image data are increasingly in demand. The fundamental challenge in image mining is to determine how low-level, pixel representation contained in a raw image or image sequence can be processed to identify high-level spatial objects and relationships. To meet this challenge, we propose an efficient information-driven framework for image mining. We distinguish four levels of information: the Pixel Level, the Object Level, the Semantic Concept Level, and the Pattern and Knowledge Level. High-dimensional indexing schemes and retrieval techniques are also included in the framework to support the flow of information among the levels. We believe this framework represents the first step towards capturing the different levels of information present in image data and addressing the issues and challenges of discovering useful patterns/knowledge from each level

Organizing and Indexing Photo Collections

Historical photo archives or collections can put an organization on the map and make it into a destination for patrons. Conversely, if not well organized and indexed, collections and archives can languish in obscurity and occupy valuable space and resources with no tangible return for the organization. The Milwaukee Public Library’s (MPL) Historic Photo Archives (HPA) contain around thirty thousand historic images; of those images, most are located in the Historic Photo Collection, one of the archives’ 45 individual collections. The HPA has evolved over the decades. Various reference librarians have been assigned the archives, and the rotation of responsible parties has left its mark. The challenge created by having many individuals with different backgrounds, priorities, areas of interest, and time to devote to the maintenance of the collection has been mitigated by a strong collection development policy

Beyond English text: Multilingual and multimedia information retrieval.

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