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Seminars Jointly Organized by School of Computing NUS, and PREMIA |
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Friday, 27 June 2008 |
 We are pleased to invite you to the following seminars: 1. Real-Time Document Image Retrieval with LLAH, by Prof. Koichi Kise, 2. Large-Scale and Real-Time Specific Object Recognition, by Prof. Koichi Kise, 3. Pattern recognition with supplementary information --- an overview and recent results, by Dr. Masakazu Iwamura.
The seminars are jointly organized by School of Computing and Pattern
Recognition and Machine Intelligence Association (PREMIA).
Date & Time:
18 July, 10.30 - 12.00 noon
Venue:
Seminar Room 2, COM1-2-4, school of Computing, NUS
Speakers:
Prof. Koichi Kise and Dr. Masakazu Iwamura
Outlines of the seminars:
Seminar 1: Real-Time Document Image Retrieval with LLAH by Prof. Koichi Kise
In
this talk I describe our image retrieval method named Locally Likely
Arrangement Hashing (LLAH). LLAH has following excellences: (1) fast
and accurate retrieval even under perspective distortion and occlusion,
(2) the captured region and skew of the document can be estimated from
correspondences of feature points subsidiarily obtained during
retrieval process. In this talk, I show a demonstration of a
real-time document image retrieval system with a DB up to 20,000 pages
in 1/7 second per query. Reference: http://imlab.jp/LLAH/.
Seminar 2: Large-Scale and Real-Time Specific Object Recognition by Prof. Koichi Kise
What will happen if we have a tool for "linking" real objects to the cyberspace? Will it be effective for solving some problems of our daily life? How can we realize such functionality? --- Barcodes or RFIDs?
In
my talk, I would like to discuss with you the possibility of realizing
such functionality by "object recognition" technologies. As an
example case, I introduce a method of large-scale (100,000 objects) and
real-time (200ms) recognition of planar objects with a cheap web
camera. A demo is also planned.
Seminar 3: Pattern recognition with supplementary information --- an overview and recent results by Dr. Masakazu Iwamura
In
pattern recognition, unavoidable error is called Bayes error, which is
caused by almost same features derived from different classes. The
royal road to decrease the Bayes error is to devise new good features. However,
it is not always possible. For example, in character recognition, "I''
and "l'' in some fonts have the identical shape, and they cannot be
distinguished by only their appearances. In order to cope with the
problem, we have proposed to introduce a "hint'' on the true class,
which is called "supplementary information''. For the problem of "I'' and "l'', a small hint that "the answer is capital letter'' is enough to recognize them. In
this talk, we present an overview and recent results of a new pattern
recognition framework which employs the supplementary information.
Short Bio:
Koichi
Kise received his B.E., M.E. and Ph.D. degrees in communication
engineering from Osaka University, Japan, in 1986, 1988, and 1991,
respectively. In 1990, he joined Osaka Prefecture University, Japan,
where he is now a Professor of Department of Computer Science and
Intelligent Systems. From 2000 to 2001, he was a visiting professor at
German Research Center for Artificial Ingelligence (DFKI), Germany. His
research interests include document image analysis, object recognition
and information retrieval. He received several domestic and
international awards including IEICE Best Paper Award in 2006,
IAPR/ICDAR2007 The Best Paper Award. He is a member of the editorial
board of IJDAR, an associate editor of pattern recognition. He has
organized several international workshops, such as CBDAR2005, CBDAR2007
and DAS2008.
Masakazu Iwamura received his B.E., M.E. and Ph.D
Engineering degrees from Tohoku University, Japan, in 1998, 2000 and
2003, respectively. He is an assistant professor at Graduate School of
Engineering, Osaka Prefecture University. His research interest
includes pattern recognition, object recognition and information
retrieval. He received IEICE Best Paper Award in 2006, IAPR/ICDAR2007
The Best Paper Award, Best Poster Award in MIRU2005, Best Demonstration
Award in MIRU2006 and MIRU2007, and Osaka Pref. Univ. President Prize
in 2006, 2007 and 2008. He is an organizing committee member of
CBDAR2005, CBDAR2007 and DAS2008, and a program committee member of
DAS2008.
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