Document Type


Date of Award


Degree Name

Master of Science in Electrical Engineering - (M.S.)


Electrical Engineering

First Advisor

Yun Q. Shi

Second Advisor

Edwin Hou

Third Advisor

Marshall Chuan Yung Kuo


Optical flow, also known as image flow, is of fundamental importance in the processing of image sequences. Various approaches to determine optical flow have been proposed --- others continue to appear. Using several sets of real image sequences, here, the results of three different approaches to the the determination of optical flow are reported, the approaches are the Gradient-based approach, the Correlation-based approach and the Correlation-feedback approach. The comparisons are primarily empirical, and they show that the performance of these different algorithms differs significantly among the different image sequences, indicating that there does not exists one superior algorithm which could be suitable to every different kind of situations. Every individual algorithm has its own advantages and limitations.

Also, recent research shows that motion analysis has many potentials in the computer vision area. There are basically two different approaches to recover structure of objects and relative motion between objects and cameras: one is the optical flow field approach and the other is the feature correspondence approach. The unified optical flow field (UOFF) [5] is a generalization of the optical flow to stereo imagery. Here, through the results obtained from the real image sequences, the feasibility of U01,1- approach to motion analysis has been shown.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.