Instructor : Bin Wang
This project aims to get a fast and better video segmentation based on machine learning.
Achieved a stable segmentation result on boundary consistency, based on the SVM training and the segmentation result of the first video frame by Mean Shift.
Implemented low-level feature extraction of images, such as variance and color, which enhanced the segmentation accuracy and robustness.
Improved the recognition of pattern repeated objects, such as zebra, by using the method of point-wise mutual information which was often used in the area of word association.