M
Mona Omidyeganeh
Researcher at University of Ottawa
Publications - 31
Citations - 538
Mona Omidyeganeh is an academic researcher from University of Ottawa. The author has contributed to research in topics: Wavelet transform & Wavelet. The author has an hindex of 11, co-authored 29 publications receiving 374 citations. Previous affiliations of Mona Omidyeganeh include National Research Council & Sharif University of Technology.
Papers
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Proceedings ArticleDOI
YawDD: a yawning detection dataset
TL;DR: This paper presents two video datasets of drivers with various facial characteristics, to be used for designing and testing algorithms and models for yawning detection, and presents the results of their own yawning Detection method.
Journal ArticleDOI
Yawning Detection Using Embedded Smart Cameras
Mona Omidyeganeh,Shervin Shirmohammadi,Shabnam Abtahi,Aasim Khurshid,Muhammad Farhan,Jacob Scharcanski,Behnoosh Hariri,Daniel Laroche,Luc Martel +8 more
TL;DR: This paper designs and implements an automatic system, using computer vision, which runs on a computationally limited embedded smart camera platform to detect yawning, and uses a significantly modified implementation of the Viola-Jones algorithm for face and mouth detections.
Proceedings ArticleDOI
Intelligent driver drowsiness detection through fusion of yawning and eye closure
TL;DR: This paper presents a robust and intelligent scheme for driver drowsiness detection employing the fusion of eye closure and yawning detection methods, and proves the high efficiency of the proposed idea.
Journal ArticleDOI
Evaluation of an automated thresholding algorithm for the quantification of paraspinal muscle composition from MRI images
TL;DR: The proposed automated thresholding algorithm to assess paraspinal muscle size and composition measurements was highly reliable, with excellent agreement with the reference manual thresholding method.
Journal ArticleDOI
Video Keyframe Analysis Using a Segment-Based Statistical Metric in a Visually Sensitive Parametric Space
TL;DR: In this article, generalized Gaussian density (GGD) parameters of wavelet transform subbands along with Kullback-Leibler distance (KLD) measurement are employed for keyframe extraction.