Statistical Saliency Model incorporating motion saliency and an application to driving

This thesis extends the Statistical Saliency Model to include motion as a feature, enabling it to compute the saliency of video sequences more effectively. The motion feature is represented as optical flow and incorporated into the model. The model is validated by testing its capability in predicting reaction time performance in a driving simulator. We find that the model does help predict reaction time and some eye-movements in some simulated driving tasks.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2008

Author dc:creator

• Raj, Alvin Andrew

Advisor dc:contributor.advisor

• Ruth Rosenholtz and Edward Adelson.

• Electrical Engineering and Computer Science.

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/1721.1/45886

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/45886