Video based system monitoring

In this work we develop new algorithms for video comparison, for video alignment, and for determining the similarity between entire video clips or detecting similarities between sub-videos. The intent of this work is to develop video-based techniques for autonomous monitoring of systems in industrial, manufacturing, and research environments. We develop an algorithm, Dynamic Time and Space Warping, to determine a model-free similarity between an example and an unknown video. The algorithm optimally shifts space and warps time according to local measures of video similarity. The resulting similarity measure is an optimal path of similarity versus space and time used to optimally align or compare the two video. We demonstrate the applicability of such similarity measures to industrial wear monitoring, failure prediction, and assembly-line feedback control and to non-industrial settings with examples in sports and entertainment. We extend the similarity machinery and introduce a new technique for video event-detection. The local similarity is integrated along the optimal space-time path in order to determine a cumulative similarity.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Mechanical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Anthony, Brian W., 1972-

Advisor dc:contributor.advisor

• Kamal Youcef-Toumi.

• Mechanical Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/38263

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/38263