NSF workshop on Visual Information Management Systems

One of the most important technologies needed across many traditional areas as well as emerging new frontiers of computing, is the management of visual information. For example, most of the Grand Challenge applications, under the High Performance Computing and Communication (HPCC) initiative, require management of large volumes of non-alphanumeric information, computations, communication, and visualization of results. Considering the growing need and interest in the organization and retrieval of visual and other non-alphanumeric information, and in order to stimulate academic projects in this area, a workshop on Visual Information Management Systems (VIMS) was sponsored by the National Science Foundation. This workshop was held in Redwood, CA, on February 24-25, 1992. The goal of the workshop was to identify major research areas that should be addressed by researchers for VIMS that would be useful in scientific, industrial, medical, environmental, educational, entertainment, and other applications.

The major findings of the workshop were that VIMS require new techniques in all aspects of databases, computer vision, and knowledge representation and management; and that such techniques are best developed in the context of concrete, practical applications. VIMS will provide impetus and testbeds for many techniques being explored for the future database systems. Researchers from image processing and understanding, knowledge representation and knowledge based systems, and databases must work very closely to develop VIMS. Such systems should be developed in the context of applications that will be of immediate interest in industrial, medical, or scientific contexts. Without concrete applications and ambitious implementation projects, most of the important and difficult issues are likely to be ignored. Considering the interdisciplinary nature of the research in this area, a few major research projects in this area are essential for its growth. Increased emphasis on HPCC by many Federal agencies can help in the rapid development of VIMS technology. Similarly, by addressing some of the Grand Challenges, research interested in VIMS can understand critical issues and develop techniques to solve them, in a concrete and useful context.

Parallel processing is essential for implementing VIMS. As is well known, the processing of images is one of the most computation-intensive tasks. For entering images in databases and for performing required operations at query time, an enormous volume of data must be processed. Parallel computing will be essential for implementing a VIMS that can insert images in reasonable time and provide fast response to user queries. The computational requirements of video databases are likely to be one of the most demanding. It is very likely that video databases will require research in highly parallel-pipelined architectures.

In interdisciplinary research areas such as VIMS, most important and difficult problems usually fall through the cracks. The three most relevant areas for the development of VIMS are: databases, computer vision, and knowledge representation. Data compression, fault-tolerant real time access to image data through networks, and parallel processing issues should be addressed in the context of databases for VIMS. VIMS should not be considered as an application of the existing state of the art in any of these fields to manage and process images. Database researchers must understand the issues specific to managing and processing images and other forms of data by granting them the same status that has been given to alphanumeric information. Computer vision researchers should identify features required for interactive image understanding, rather than their discipline's current emphasis on automatic techniques, and develop techniques to compute features in interactive environments. Most knowledge representation research has been concerned with symbolic k knowledge. For VIMS and HPCC applications, techniques for representing symbolic and non-symbolic representations at the same level will be required. Reasoning approaches that can deal with such representations will be useful not only in VIMS, but in many other applications also. Finally, performance issues pose a significant challenge in all aspects of VIMS, from memory organization to information retrieval.