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/