Western University Computer ScienceWestern Science

MSc Thesis Defense

 

Seyed Jamal Zabihi

Detection and Recognition of Traffic Signs Inside the Attentional Visual Field of Drivers

 

Date:
Time:
Place:
Supervisor:
Thesis Examiners:

Extra-Departmental
Examiner:
Chair:
Friday, March 10, 2017
10:00 a.m.
Middlesex College, Room 320
Dr. Steven Beauchemin
Dr. Mark Daley
Dr. Olga Veksler

Dr. Quazi Rahman (ECE)
Dr. Bob Webber

 

Abstract:

Traffic sign detection and recognition systems are essential components of Advanced Driver Assistance Systems and self-driving vehicles. In this contribution we present a vision-based framework which detects and recognizes traffic signs inside the attentional visual field of drivers. This technique takes advantage of the driver 3D absolute gaze point obtained through the combined use of a front-view stereo imaging system and a non-contact 3D gaze tracker. We used a linear Support Vector Machine as a classifier and a Histogram of Oriented Gradient as features for detection. Recognition is performed by using Scale Invariant Feature Transforms and color information. Our technique detects and recognizes signs which are in the field of view of the driver and also provides indication when one or more signs have been missed by the driver.