Undergraduates interested in computer vision or multi-modal multi-media data modeling which currently includes projects grounded in biology and astronomy should contact Kobus by E-mail (kobus AT cs DOT arizona DOT edu). More information about the activities of the lab in general is available here.
Students who have participated in vision lab as undergraduates include Matthew Johnson (honor's student, graduated December 2003), Abin Shahab (honor's student, graduated May 2004), Ekatarina (Kate) Spriggs, Juhanni Torkkola, and Bobby Dionne.
Some of the projects that have involved undergraduates are showcased below.
To the right is a labeled model of the fungus Alternaria generated by a
stochastic L-system built by undgraduate researcher
Kate Spriggs
. For more information, follow this
link.
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A screen shot of a program for browsing large digital art image databases that
is being developed by undergraduate students in computer science at the U of A.
(Art images courtesy of the Fine Arts Museum of San Francisco).
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Many words in natural language are ambiguous as illustrated here by the word
"bank". Typically, resolving such ambiguity is attempted by looking at nearby
words in the passage being analyzed. U of A undergraduate students in computer
science have played a key role in the development of a novel method for adding
information from accompanying illustrations to help reduce the ambiguity. The
system learns from a data base of images that certain word senses (e.g.,
meanings of bank found with outdoor photos), are associated with certain kinds
of image features. This association is then used to incorporate information in
illustrations to help disambiguate the word under consideration.
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These three images illustrate contributions made by computer science students
to the U A multi-department effort to compete in international aerial robotics
competition which is largely an event for undergraduates. Here computer
controlled planes and/or helicopters work towards accomplishing a mission
specified by the contest organizers. Part of the current task is to find a
building having a particular symbol on it (a), and identify the the doors and
windows of that building, and then identify which doors and windows are open so
that a sub-vehicle can be launched through the portal. Figure (b) shows the
symbol identification software being tested from a moving vehicle to simulate
flight. Figure (c) shows a view from the computer science department with lines
found in this image and the matching lines found in a companion image. The
students use the shift (shown in green) between matching edges to estimate the
distance to the edge, which is used to help analyze the structures.
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(a)
(b)
(c)
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Two images which have been segmented by three different methods. U of A
undergraduate students in computer science are involved in research to
evaluate the quality of such methods. Segmentation quality is quantified by
the degree to which the regions are useful to programs which automatically
recognize what is in the images.
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