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Education: Computer Science and Engineering, Michigan State University, MS and PhD Employment: Department of Computer Science and Information Engineering National Taiwan Normal University Address: 116 No. 88, Sec. 4, Ting-Chow Rd., Taipei, Taiwan, R.O.C. Contact: Tel: 886-2-77346661 Fax: 886-2-2932-2378 E-mail: schen@csie.ntnu.edu.tw Research Interests: Computer Vision, Image Processing, Pattern Recognition, Artificial Neural Networks, Fuzzy Systems, Intelligent Transportation Systems Academic Memberships: IEEE Senior Member (1997), IET Fellow (2012)
In 1990, Professor Sei-Wang Chen was with Department of Information and Computer Education
(ICE) at National Taiwan Normal University (NTNU) as Associate Professor and soon promoted
to Full Professor in 1993. Founded in 1946, NTNU is a vibrant learning community that has
long been recognized as one of Taiwan¡¦s elite institutions of higher education. NTNU is
selected by ROC Ministry of Education (MOE) as one of the top ten universities in Taiwan,
where there are about 160 universities. During his serving in NTNU, Professor Chen and his
colleague, Professor Lin, were designated by the University to found Graduate Institute of
Computer Science and Information Engineering (CSIE) in 2001, which was later renamed as
Department of CSIE in 2006. Prof. Chen was elected to be the Chairperson of CSIE in 2005.
Currently, the department has 16 full-time faculties, about 200 undergraduate and 150
graduate students, offering Bachelor, Master and Doctoral degrees in various fields of
computer science and engineering. Prof. Chen has hence received the Excellent Teaching
Qualification from NTNU, the Education Service Award from MOE, and been appointed as the
commissioner of Science Education Committee by MOE in recognition of his prominent
performances in both education and leadership.
Prof. Chen has established himself as a world-class scholar and been highly active and
regarded in his professional area. He has joined a number of academic societies, including
IEEE Computer Society (1983), Institution of Engineering and Technology (IET) Society (2012),
Pattern Recognition Society (1986), Chinese Image Processing and Pattern Recognition (CIPPR)
Society (1990), and Intelligent Transportation Systems¡VTaiwan Society (2001), and has
heavily engaged in the associated activities and affairs. To address a few, he has served
as the General Chairs of the 11th Conference on Computer Vision, Graphics,
and Image Processing (CVGIP) in 1998 and the 1st Symposium on Intelligent
Transportation Systems (ITS) in 2004. Of which, the CVGIP conference is one of the most
important Chinese conferences, which is mainly sponsored by the CIPPR Society that is
now the largest professional community in Taiwan. Prof. Chen has also served as the
Session Chairs of 1990-2012 Conferences on CVGIP, 2011 IEEE International Conference
on Intelligent Transportation Systems, 2004 IEEE International Conference on Cybernetic
and Intelligent Systems, and 2000 Asian Conference on Computer Vision. Also, he has
been on the program committees of numerous domestic and international conferences.
Prof. Chen was elected to the grades of IEEE Senior Member in 1997 and the IET Fellow
in 2012.
Prof. Chen is an exceptionally talented scientist with wide research interests including
image understanding, scene interpretation, computer vision, pattern recognition, artificial
neural networks, and Fuzzy systems. The main applications are on intelligent transportation
systems, automatic lecture recording systems, and their related. His strength in research
is evident from the large number of high-quality papers he has published. He has issued 54
refereed papers including some presented at the prestigious journals of IEEE Trans. on
Intelligent Transportation Systems (ITS), Vehicular Technology (VT), Signal Processing (SP),
Neural Networks (NN), and Systems, Man and Cybernetics (SMC),and the international journals
of Parallel Computing (PC), Pattern Recognition (PR), and Computer Vision, Graphics, and
Image Processing (CVGIP): Image Understanding, and Graphical Models and Image Processing.
Besides, he has published 134 conference papers and 24 technical reports. Recently, an
assessment report entitled, Literature, ¡§A Bibliographic Analysis of the IEEE Trans. on
Intelligent Transportation Systems Recognition (PR), and issued in (IEEE Trans. on ITS, Vol.
11, No. 2, pp. 251-255, 2010) indicates that Prof. Chen¡¦s paper entitled,¡§Automatic License
Plate Recognition,¡¨ published in 2004 earned second in the rank of most cited papers among
405 papers published in the IEEE Trans. on ITS during the past decade, in which 1001 authors,
457 research institutions and 36 countries are involved. Moreover, NTNU gained fifth in the
rank of most cited institutions and Taiwan acquired ranks 4 and 3 of paper counts and
high-impact countries, respectively. As indicated, Prof. Chen¡¦s work on intelligent
transportation systems has to some extent made a significant impact on the field.
Prof. Chen has been the Director of Image Processing and Computer Vision ¡V Intelligent
Transportation Systems (IPCV-ITS) Lab since 1990. Three associate professors and two
assistant professors have been with the Lab. Currently, the Lab consists of two associate
professor, one assistant professor, three Ph.D. students, and eleven M.S. students. Forty
seven group members of the Lab have successfully earned their graduate degrees (three Ph.D.
and 44 M.S.). Prof. Chen has gained his research financial support from numerous NSC and
domestic as well as international industrial-academic cooperation projects. The following
numerates some of his significant contributions.
(1) A computational model, referred to as the dynamic visual model (DVM), inspired by human
cognitive processing and selective attention, has been proposed for ITS applications. This
model consists of three components, referred to as the sensory, perceptual, and conceptual
analyzers. Two neural modules, a spatiotemporal attention neural network and an assembly of
adaptive resonance theory neural networks, are developed to perform perceptual and conceptual
analyses, respectively. A memory, called the episodic memory, coordinates the three analyzers.
This model exhibits a number of intriguing features such as, hierarchical processing,
configurability, adaptive response, and selective attention. The DVM has been embedded
in a vision-based driver assistance system for performing ¡§Automatic Change Detection
of Driving Environments¡¨ and ¡§Critical Motion Detection of nearby Moving Vehicles.
¡¨These two works have been published in IEEE Trans. on Intelligent Transportation
Systems and IEEE Trans. on Neural Networks, respectively.
(2) Many drowsy-related traffic accidents have been reported every year. Drowsiness that
declines visual sensibility, situational decision-making capability can significantly
degrade the performance of a driver. In the work entitled, ¡§Sleep Technology for Driving
Safety,¡¨ a vision system motivated by the human visual system that can effortlessly
identify the vigilance level of a person is developed for monitoring driver¡¦s
fatigue/drowsiness while driving. The system achieves the purpose based on the facial
expressions of the driver. A number of facial parameters, including percentage of eye
closure over time, average eye closure duration, eye blinking frequency, degree of gaze,
average mouth openness duration, and head nodding frequency, are calculated for categorizing
facial expressions into different levels of vigilance. This work has been collected in
the book entitled,¡§Introduction to Sleep Technology,¡¨ edited by S. C. Kang and
R. P. Y. Chiang, Springer, Netherlands, 2011.
(3) License plate recognition (LPR) plays an important role in many ITS applications.
Although a large number of techniques have been proposed, most of them worked under
restricted conditions such as, stationary background, fixed illumination, designated
area, and limited vehicle speed. The proposed LPR technique characterized by fuzzy
disciplines as well as neural subjects has comparable performance with the
state-of-the-art techniques but with fewer constraints on the working environments.
(4) Several systems under operation or development include: i) Pedestrian Detection
and Tracking at Crossroads (Pattern Recognition Journal), ii) Video Stabilization for
a Camcorder Mounted on a Moving Vehicle (IEEE Trans. on VT), iii) Real-Time Generation
of Orthographic-View Surround Images of a Vehicle (Under Reviewing), iv) Smart Cameras
for ITS Applications (Industry-Academy Joint Project), v) Motorcycle Management System
on Campus (Industry-Academy Joint Project), vi) Active Driving Safety Assistance System
(NSC Project), vii) Intelligent Indoor Parking Management System (NSC Project), and
viii) Vision-Based Traffic Monitoring System, to name a few.
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