Anup Basu, PhD

Professor, Faculty of Science - Computing Science

Contact

Professor, Faculty of Science - Computing Science
Email
basu@ualberta.ca

Overview

About

Education

  • B.S., Math & Statistics, Indian Statistical Institute (Calcutta), 1980
  • M.E., Computer Science, Indian Statistical Institute (Calcutta), 1983 
  • Ph.D., Computing Science, University of Maryland, 1990

Fellowships

  • American Neurological Association

Chair Positions

  • AITF Industrial Chair in Multimedia
  • General Chair, IEEE International Conference on SMC 2017, Banff, Canada
  • Industrial Chair, IEEE International Conference on Systems, Man & Cybernetics (SMC) 2014, San Diego, California
  • General Chair, IEEE International Conference on Multimedia & Expo (ICME) 2013, San Jose, California


Research

Areas

Computer Graphics
Computer Vision and Multimedia Communications

Interests

3D Computer Vision & Graphics, Multimedia, Networks.

Summary

The focus of my present academic research is in Quality of Service (QoS) based delivery of Multimedia for Electronic Commerce and TeleLearning. For both these applications it is necessary to adaptively use the bandwidth available and provide the best possible quality according to user priority specifications. I have developed a statistical approach for "Optimal Bandwidth Monitoring" for single server connections as well as for distributed multimedia retrieval. The approach provides an estimation based on statistical confidence level and has shown to produce expected results based on real network tests.

In the context of online 2D & 3D visualization, I am developing JAVA Applet based tools for interactive viewing of Super High Resolution & 3D images; this work is being supported by TelePhotogenics Inc. and the National Research Council of Canada. More importantly, I raised substantial industrial funding to build a Super High Resolution digital camera and have designed patented and patent pending technologies for new SHR Stereo and 3D scanners.

I have also been active in the Synthetic Natural Hybrid Coding (SNHC) component of MPEG-4 coding. SNHC is part of Working Group 11 (WG11) in MPEG-4. Specifically, I have been working on detection and tracking of facial features, and displaying such information in a videoconferencing scenario through model-based coding and transmission. I am also investigating displaying head-and-shoulder models in stereo. This research will be further supported by the installation of a major equipment facility, the "CAVE", which uses rear projection of stereo images on to 3 walls.

In the past, I initiated the applications of variable resolution (or foveation) emulating the animate visual systems for image compression and communication. Results have shown how intelligent pre-processing of images can not only lead to improved videoconferencing systems but can also enhance the quality of standard compression algorithms, such JPEG, MPEG, and Wavelets. The results are especially useful for communication at low bit-rates. I have also demonstrated the advantage of "intelligent" cell loss for image/video data transmitted over congested ATM networks. The work will have an influence on the emerging area of Multimedia ATM design. My publications clearly shows that the traditional approach of treating all types of information as just a stream of bits in ATM switches is inadequate for congested networks. My work on foveated image compression and stereo visualization has been referenced and extended by several groups of researchers at New York University, Simon Fraser University and University of Texas at Austin.

I have been the lead applicant in several projects including an Imaging Systems Curriculum initiative funded by Hewlett-Packard with $365,000 in equipment & a recent ASRA/TelePhotogenics/IBM/Keeweetinok Lakes RHA 3D Medical Imaging initiative that has received over $2 M in cash and in-kind funding.

Courses

CMPUT 414 - Introduction to Multimedia Technology

Introduction to basic principles and algorithms used in multimedia systems. Students obtain hands-on experience in issues relating to multimedia data representation, compression, processing, and animation. Topics will be selected from image and video coding and transmission, animation, human perceptual issues associated to multimedia technologies. Prerequisites: CMPUT 206 or 306; CMPUT 307 or 411; knowledge of second-year level MATH/STAT; Java, C, or equivalent programming or consent of instructor.

Fall Term 2020
CMPUT 499 - Topics in Computing Science

This topics course is designed for a one on one individual study course between a student and an instructor. Prerequisites are determined by the instructor in the course outline. See Note (3) above.

Fall Term 2020
CMPUT 605 - Topics in Computing Science

Fall Term 2020
CMPUT 606 - Topics in Computing Science

Fall Term 2020

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