Thesis Defense Announcement for Benjamin James Bartlett – 03/23/2022 at 9:30 AM
March 2, 2022
Title: Recognizing Human Motions Through Automotive Sensors
When: Wednesday, March 23rd at 9:30am
Where: Cisco Webex
https://msstate.webex.com/msstate/j.php?MTID=m2d331ebc4cfafa06ad19cac9fde8f41e
Candidate: Benjamin James Bartlett
Degree: Masters, Electrical and Computer Engineering
Committee:
Dr. Ali Gurbuz
(Major Professor)
Dr. John Ball
(Committee Member)
Dr. Bo Tang
(Committee Member)
Abstract:
As technology advances with each new day, so do the applications and uses of the different modalities of technology, including transportation, particularly in advanced driver-assisted systems (ADAS) vehicles. These systems allow the vehicle to avoid collisions, change lanes, adjust the vehicle’s speed, and more without the need of driver input. However, each sensor type has a weakness, and most ADAS vehicles rely heavily on visual sensors, such as RGB cameras and LiDAR sensors. These visual-based sensors may collect very noisy data in cloudy, raining, foggy, or other obscuring phenomena. Radar, on the other hand, does not rely on visual information to produce meaningful output. This research aims to use radar technology for human motion classification using traffic signaling based on motions generally used in the American traffic system, while also fusing data from other visual sensors and validating results using neural networks.