Full-Frame Video Stabilization with Large Moving Object

• Main Authors: Wei-Ting Huang, 黃惟婷
• Other Authors: 陳炳宇
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/27680320781860145678

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 96 === This thesis presents an approach to post-processing casually captured videos to improve apparent camera movement. A lot of home videos have some problems about the artifacts like hand shaking when capturing without tripod. Video stabilization is an important technique to solve this problem. However, the technique does not work very well in some situations such as the larger foreground, incomplete background or other situations,etc. In this thesis,we propose a novel method of video stabilization to overcome the situations with the larger foreground, or the feature points amount of the background is less then of foreground and some camera motion such as zoom in and zoom out. This system applies a method, optical flow, to estimate the motion vector of all pixels between each pair frames. Then, we use K-means clustering to group the similar motion vectors of each frame. To select an adequate segment to estimate the global camera path of video could obtain one more correct global camera path. After motion vector segmentation and camera path estimation, we could stitch all of video frames to get a panorama and estimate the range of moving object we can recover by neighbor frames. Based on the background panorama and moving object recovered range, we could find some new paths which would lose information less. After the above operations, a full-stabilized video could be achieved.