Developing fast and unbiased computer vision algorithms – UROP Spring Symposium 2021

Developing fast and unbiased computer vision algorithms

Aina Zaidi


Pronouns: she/her

Research Mentor(s): Carol Flannagan, Research Professor
Research Mentor School/College/Department: University of Michigan Transportation Research Institute, College of Engineering
Presentation Date: Thursday, April 22, 2021
Session: Session 1 (10am-10:50am)
Breakout Room: Room 16
Presenter: 3

Event Link


In an effort to improve driver safety and autonomous vehicle testing, video recordings of drivers allow for data to be analyzed. These videos are first examined by human coders, but a more efficient, automated algorithm would prevent the need for human coders entirely. However, in order to build the algorithm, human coders need to analyze videos of drivers and label various actions, such as if the driver is turning or tilting their head, or hand movements, such as texting, and if their hand is obscured. Once these labels are implemented, they are tested against each other for accuracy, so that the final algorithm is unbiased enough to be implemented into vehicle safety.

Authors: Carol Flannagan, Aina Zaidi
Research Method: Data Collection and Analysis

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