DIMACS Workshop on Video Mining November 4-6, 2002 DIMACS Center, Rutgers University, Piscataway, New Jersey Organizers: Azriel Rosenfeld, University of Maryland, ar@cfar.umd.edu Daniel DeMenthon, University of Maryland, daniel@cfar.umd.edu Dave Doermann, University of Maryland, doermann@cfar.umd.edu Presented under the auspices of the Special Focus on Data Analysis and Mining. Modern computer technology, together with the proliferation of broadcast channels and of video-based surveillance systems has enabled us to produce vast amounts of both raw and processed video data. The potential uses of this data are many and varied. Monitoring and mining of the content of this already huge, rapidly growing mass of data calls for the development of major computational resources and the development of sophisticated video understanding techniques. The applications and potential applications of video mining include: - monitoring of (possibly remote) surveillance cameras in theft protection, fire protection, care of bedridden patients and young children - automatic recognition of suspicious people in large crowds - automatic checking to identify passengers entering an airplane, bus, or public building (to verify entry authorization) - recognition of people by fingerprints, hand prints, and eye patterns - automatic quality control in manufacturing processes - robotic vision - reconstruction of anatomical data by means of visual slices taken by magnetic resonance imaging machines - medical diagnosis and remote performance of medical procedures - analysis of DNA and protein structures - analysis of gas/oil drilling data and/or seismic data to identify potential new sources of gas/oil - monitoring seismic patterns to detect earthquakes and/or nuclear tests - retrieval of archived video clips to illustrate a newsbreaking story - retrieval of suspicious activities in prerecorded video surveillance sequences - browsing of DVD and set-top box recordings - intelligent fast-forward techniques - detection of multi-lingual scene text to determine origin of broadcast - Video search engines for web browsers - ranking of video clips by relevance in web query results - classification of videos into genres for search pruning - detection of crowd patterns for mob control - detection of traffic patterns for traffic understanding management There are some pervasive challenges here. A huge amount of data must be efficiently stored. Once stored, there must exist efficient retrieval algorithms. It must also be possible to retrieve different kinds of data stored in possibly different formats. Some of the applications will require real-time response and action based on an incoming data stream. The purpose of this workshop will be to survey available and potential technologies for video monitoring and mining (and in general methods of fast and efficient content-based analysis of video streams) and to identify promising directions for research in this challenging area. Specific topics to be covered will be analysis of camera motion and scene activity; temporal segmentation; content-based classification, indexing, and retrieval; representation, browsing, and visualization. We will also investigate related mining problems having to do with audio mining, texture mining, seismic data mining, and cross-modality mining. Audio mining applications of interest include speech recognition; texture mining applications include analysis and recognition of materials; seismic data mining applications include identification of potential new sources of oil and gas and detection of earthquakes and/or nuclear tests. Cross-modality issues arise for example in problems involving identification from both video and speech. Papers should be submitted in hard copy to the Organizers at Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742-3251. They can also be submitted by email; text and images can be in latex, word, pdf, or postscript and video can be in mpeg, quicktime or avi. Material must be submitted by July 1, 2002. Authors will be notified about acceptance decisions at the beginning of August. Our funding agencies require that we charge a registration fee during the course of the workshop. Registration fees include participation in the workshop, all workshop materials, breakfast, lunch, breaks and any scheduled social events (if applicable). Fees are $40 per person per day for faculty, researchers and "other", and $5 per person per day for postdocs. However, the registration fee is waived for undergraduate students, graduate students, DIMACS postdocs and DIMACS long-term visitors who are in residence at DIMACS. The registration fees for employees of DIMACS partner institutions are waived as well. DIMACS partner institutions are: Rutgers University, Princeton University, AT&T Labs - Research, Bell Labs, NEC Research Institute and Telcordia Technologies. For complete information on registration, travel and accommodations see: http://dimacs.rutgers.edu/Workshops/Video/