Faculty
Name:Chih-Yuan Yao
Department:Computer Science and Information Engineering
Office:RB501Phone:02-27376936
Email:cyuan.yao@gmail.com
Research Interest:

Computer graphics, including mesh processing and modeling, and non-photorealistic rendering (NPR).

Detail

Name:Yu-Chi Lai
Department:Computer Science and Information Engineering
Office:E1-222-3Phone:+886-2-2730-3665
Email:cheeryuchi@gmail.com
Research Interest:

Computer Graphics, Computer Games and Computer Vision

Detail

Name:Kai-Lung Hua
Department:Computer Science and Information Engineering
Office:E1-222-4Phone:+886-2-2730-3664
Email:hua@mail.ntust.edu.tw
Research Interest:

Digital Image and Video Processing, Computer Vision, Multimedia Networking

Detail

Name:Da-Yuan Huang
Department:Computer Science and Information Engineering
Office:- Phone:1-603-359-1868
Email:dayuan.huang.tw@gmail.com
Research Interest:
Human-Computer Interaction, Intenet of Things Interface, and Wearable Interface. 

Detail

Name:Shanq-Jang Ruan
Department:Electronic and Computer Engineering
Office:IB 715Phone:+886-2-2737-6411
Email:sjruan@mail.ntust.edu.tw
Research Interest:

Energey-Efficient Image Processing, Low power EDA/VLSI, Embedded Systems Design 

Detail

Name:Chang Hong Lin
Department:Department of Electronic and Computer Engineering
Office:IB-701-1Phone:+886-2-2737-6397
Email:chlin@mail.ntust.edu.tw
Research Interest:
Real-time human action analysis, power and thermal-aware VLSI design, distributed smart cameras, service-oriented architecture, next generation computer architecture

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Research Projects
Title:Geological Data Visualization
Description:A picture say a thousand words. Human is good at interpreting data from visualizing a set of numbers instead of number itself. In this project we try to help geologists develop a system to visualize the data collected.

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Title:College Student Projects
Description:College students can join different kinds of projects

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Title:Background Extraction
Description:Background extraction is generally the first step for many computer vision and augmented reality applications. Most existing methods, which assume a clean background shot, are not suitable for video sequences such as highway traffic videos containing complex foreground movements which may not have a clean background shot. Therefore, this projects focuses on developing algorithms for robust background extraction.

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Course