Irene Cheng, PhD

Program Director, Faculty of Science - MSc Multimedia

Contact

Program Director, Faculty of Science - MSc Multimedia
Email
locheng@ualberta.ca

Overview

Area of Study / Keywords

Human perception and intelligence in multimedia computing Multimedia data science Healthcare Signal analysis Adaptive learning


About

Education

  • Post Doc, Computer and Information Science (CIS), University of Pennsylvania, 2007
  • Ph.D., Computing Science, University of Alberta, 2005
  • M.Sc., Computing Science, University of Alberta, 1999
  • B.Sc., Computing Science, University of Alberta, 1996

Additional Positions

  • Scientific Director, Multimedia Research Centre 
  • Director, Masters with Specialization in Multimedia Program website: http://mmgrad.org/
  • Adjunct Professor, Computing Science
  • Research Affiliate, Glenrose Rehabilitation Hospital
  • NSERC Computer Science Evaluation Group committee member

Research

Personal website

Multimedia Research Group: http://crome.cs.ualberta.ca/mrc/

Areas

Human Perception in Data Science

Multimedia Graphics & Visualization

Computer Vision, Pattern Recognition and Multimedia Communications

Interests

My research interests include multimedia data transmission and Quality of Experience (QoE), mesh simplification and Levels-of-Detail, 3DTV, 3D textured mesh visualization, image processing and adaptive learning/assessment. I introduced the concept of Just-Noticeable-Difference (JND) and Relative Change on 3D TexMesh in the scale-space domain - validated following psychophysical two-alternative-choice methodology.

Summary

My research focus is on the analysis of multimedia patterns and their human perceptual impacts on real-world applications, e.g., animation, education, surveillance and healthcare. My techniques are built upon mathematical formulations like Random-Walks, Set Partitioning in Hierarchical Tree (SPIHT), Conditional Random Field (CRF), Scale-Space Filtering and Just-Noticeable-Difference (JND). Projects include: Improved automatic multi-exposure image fusion and correspondence; introduced perceptually enhanced techniques for automatic segmentation using visual cues and for enhancing medical or photographic image quality; motion capture data compression and transmission; multi-object tracking. The Computer Reinforced Online Multimedia Education (CROME) framework, which focused on adaptive learning/assessment, was designed and prototyped during the period from 2006-2012. More recent research is focused on Intelligent Analysis of Signal Decomposition and Aggregation in different application domains, which include satellite signal (InSAR) filtering and coherence estimation, LiDAR point cloud modelling, Parkinson's Disease progress tracking, vital sign pattern recognition and pressure injury monitoring.

Announcements

The MSc with Specialization in Multimedia Program provides students opportunities to work on practical applied projects with industries, and provides companies with skillful & knowledgeable students to participate in company projects. Visit http://www.mmgrad.org for detail.

Courses

MM 802 - Multimedia Communications

As a result of the advances in network infrastructures and increasing user participation in social media using displays ranging from IMAX theatres to home entertainment systems, and from desktops to handheld devices, problems associated with multimedia content encoding, e.g., HEVC, synchronization, scheduling and delivery, on top of potential packet loss, have increased significantly. These issues are particularly challenging in real-time applications. This course focuses on time and space optimization techniques with the goal to achieve Quality of Service (QoS) and Quality of Experience (QoE), taking perceptual quality into consideration, to support the communication and visualization of multimedia content transmitted over reliable as well as unreliable networks. Sections offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Winter Term 2023

MM 803 - Image and Video Processing

Quality assessment of image and video (or 3D data) is essential in many applications, which deliver educational content, medical images, games, movies, video-on-demand and so on. In order to generate high quality image and video, especially given the sheer volume of consumer demand and under constrained resources, e.g., time and bandwidth, it is necessary to understand the image and video processing pipeline from the initial creation limitations to the final display at the receiver. This course focuses on reviewing various image/video processing techniques, as well as the quality assessment metrics proposed in the literature. Sections offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Fall Term 2022

MM 804 - Graphics and Animation

Developing appealing graphics and animations has become a requirement in many industrial applications like entertainment, advertising and online education. Animation is effective in explaining abstract concepts in biology, physics and medicine. 3D graphics and simulation is also beneficial in surgical training and planning. This course is intended to provide discussions on graphics and animation techniques, including 3D data acquisition, processing, transmission and rendering. Students will have the opportunity to understand and compare various state-of-the-art techniques in 3D modeling, animation and special effects. Sections offered in a Sections may be offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Winter Term 2023

MM 805 - Computer Vision and 3DTV

While traditional image and video remain at the core of multimedia content, 3D video is perceived as the next generation in video technology. 3D video incorporates the depth perspective which enables viewers to feel immersed in a more realistic environment. This course provides students with the latest 2D and 3D video developments and in particular relating to stereoscopic and multi- view with or without special eye-wear. Many of the techniques proposed on 3D video inherit much of the strengths from 2D video methods and computer vision techniques. The 3D component is also included in the latest HEVC standard. This course will focus on literature review and survey of these techniques. Group studies, discussions and presentations constitute the main thrust of the course. Sections may be offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Winter Term 2023

MM 806 - Virtual Reality and Tele-Presence

Virtual reality and augmented reality can provide an immersive environment where many scenarios can be simulated. For example, manufacturing and engineering tasks, medical planning and training, art and design, rehabilitation, Physics, Biology and Chemistry concept exploration and many others can benefit from a virtual reality environment . This course focuses on the challenges of setting up a user friendly virtual reality scene where users can interact in an intuitive and natural way. The use of interactive techniques and sensor-based devices, such as haptic and head-mount display, in creating a virtual environment for scientific analysis, visualization exploration and Tele-presence, as well as how mobile users can participate in these applications, will be discussed. Sections offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Fall Term 2022

MM 807 - Multimedia Project I

Sections offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Fall Term 2022 Fall Term 2022 Winter Term 2023 Winter Term 2023

MM 808 - Multimedia Project II

Sections offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Fall Term 2022 Fall Term 2022

MM 811 - AI in Multimedia

Artificial Intelligence (AI) in multimedia covers a wide range of topics. In general, it means simulating human intelligence using computer algorithms. This course introduces a high level understanding of machine learning/deep learning, which is a branch of AI. The instructor may decide to include reinforcement learning and other aspects of neural networks, as well as natural language processing depending on the course schedule. Sections offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar.

Fall Term 2022

Browse more courses taught by Irene Cheng

Scholarly Activities

Other - Advisory Board Member

Started: 2019

Alberta Artificial Intelligence Association (Alberta AI)


Research - Associate Editor

2015 to 2018

IEEE SMC Transactions on Human-Machine Systems


Research - Chair

2009 to 2011

IEEE Northern Canada Section, Engineering in Medicine and Biological Science (EMBS) Chapter 


Research - Committee Member

2011 to 2019

IEEE ICME Steering Committee


Research - Committee Member

2020 to 2023

NSERC DG Computer Science Evaluation Group 


Research - Director of the Review Editorial Board/ Chair of the Interest Group on Quality of Experience

2010 to 2014

IEEE Communication Society, Multimedia Communication Technical Committee (MMTC)


Research - General Chair (2011)/ Technical Chair (2013)

IEEE International Conference on Multimedia (ICME)


Research - IEEE SMC 2017 Technical Program Chair


Research - Mitacs College of Reviewers

Started: 2010

Mathematics of Info Tech & Complex Systems, Accelerate Program


Admin - VP, Board of Directors

2017 to 2020

Norwood Chinese Education Association

Publications

IGS-CMAES: A Two-Stage Optimization for Ground Deformation and DEM Error Estimation in Time Series InSAR Data

Author(s): Xinyao Sun, Aaron Zimmer, Subhayan Mukherjee, Parwant Ghuman and Irene Cheng
Publication Date: 7/3/2021
Publication: MDPI Remote Sensing Special Issue: Earth Environment Monitoring with Advanced Space-borne Synthetic Aperture Radar: New Architectures, Operational Modes and Processing Techniques
Volume: 13
Issue: 13
Page Numbers: 2615
DOI: 10.3390/rs13132615
External Link: https://www.mdpi.com/2072-4292/13/13/2615

Marker-less 3d Object Recognition and 6d Pose Estimation for Homogeneous Textureless Objects: an RGB-D Approach

Author(s): N. Hajari, Gabriel Lugo Bustillo, Harsh Sharma, Irene Cheng
Publication Date: 9/7/2020
Publication: MDPI Sensor, 2020 Sep. 20(18),
Volume: 20
Issue: 18
External Link: https://www.mdpi.com/1424-8220/20/18/5098

An Unsupervised Generative Neural Approach for InSAR Phase Filtering and Coherence Estimation

Author(s): S. Mukherjee, A. Zimmer, X.Y. Sun, P. Ghuman, I. Cheng
Publication Date: 7/31/2020
Publication: IEEE Geoscience and Remote Sensing Letters
Page Numbers: 1-5
External Link: https://ieeexplore.ieee.org/document/9153855

DeepInSAR: A Deep Learning Framework for SAR Interferometric Phase Restoration and Coherence Estimation

Author(s): X.Y. Sun, A. Zimmer, S. Mukherjee, Navaneeth KK, P. Ghuman, I. Cheng
Publication Date: 7/21/2020
Publication: MDPI Remote Sensing
Volume: 12
Issue: 14
Page Numbers: 2340
External Link: https://www.mdpi.com/2072-4292/12/14/2340

A color intensity invariant low-level feature optimization framework for image quality assessment

Author(s): Navaneeth Kamballur Kottayil, I. Cheng, Frederic Dufaux and A. Basu
Publication: Springer - Signal, Image and Video Processing
Page Numbers: 1-8
External Link: http://link.springer.com/article/10.1007/s11760-016-0873-x

A Multi-Sensor Technique for Gesture Recognition through Intelligent Skeletal Pose Analysis

Author(s): N. Rossol, I. Cheng and A. Basu
Publication: IEEE Transactions on Human-Machine Systems
Volume: 46
Issue: 3
Page Numbers: 1-10

Adaptive Online Transmission of 3D TexMesh Using Scale-space and Visual Perception Analysis

Author(s): I. Cheng and P. Boulanger
Publication: IEEE Transactions on Multimedia
Volume: 8
Issue: 3
Page Numbers: 550-563

Generalized Random Walks for Fusion of Multi-Exposure Images

Author(s): R. Shen, I. Cheng, J. Shi and A. Basu
Publication: IEEE Transactions on Image Processing
Volume: 20
Issue: 12
Page Numbers: 3634-3646

Image Registration based on Stochastic Graph Perturbation

Author(s): C. Leng, W. Xu, I. Cheng and A. Basu
Publication: IEEE Transactions on Image Processing
Volume: 24
Issue: 12
Page Numbers: 4862-4875

Perceptually Coded Transmission for Arbitrary 3D Objects over Burst Packet Loss Channels and a Generic JND Formulation

Author(s): I. Cheng, L. Ying and A. Basu
Publication: IEEE Journal on Selected Areas in Communications
Volume: 30
Issue: 7
Page Numbers: 1184-1192

Stochastic process for white matter injury detection in preterm neonates

Author(s): I. Cheng, Steven P. Miller, Emma G. Duerden, Kaiyu Sun, Vann Chau, Elysia Adams, Kenneth J. Poskitt, Helen M. Branson, Anup Basu
Publication: Elsevier Journal NeuroImage: Clinical
Volume: 7
Page Numbers: 622-630
External Link: http://www.sciencedirect.com/science/article/pii/S2213158215000339