Human perception and intelligence in multimedia computing Multimedia data science
Human Perception in Data Science
Multimedia Graphics & Visualization
Computer Vision, Pattern Recognition and Multimedia Communications
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.
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). Recent 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.
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.