Abstract
Three-dimensional (3D) sensors provide the ability to perform contactless measurements of objects and distances that are within their field of view. Unlike traditional two-dimensional (2D) cameras, which only provide RGB data about objects within a scene, 3D sensors are able to directly provide depth information for objects within a scene. Of these 3D sensing technologies, Time-of-Flight (ToF) sensors are becoming more compact which allows them to be more easily integrated with other devices and to find use in more applications. ToF sensors also provide several benefits over other 3D sensing technologies that increase the types of applications where ToF sensors can be used. For example, over the last decade, ToF sensors have become more widely used in applications such as 3D scanning, drone positioning, robotics, logistics, structural health monitoring, and road surveillance. To further extend the applications where ToF sensors can be employed, this work focuses on how to improve the performance of ToF sensors by suppressing and mitigating the effects of noise artifacts that are associated with ToF sensors. These issues include multipath interference, motion blur, and multicamera interference in 3D depth maps and point clouds.
Degree Date
Fall 2023
Document Type
Dissertation
Degree Name
Ph.D.
Department
Electrical and Computer Engineering
Advisor
Dr. Dinesh Rajan
Subject Area
Electrical, Electronics Engineering, Computer Engineering
Recommended Citation
Rodriguez, Bryan, "Modeling and Compensating of Noise in Time-of-Flight Sensors" (2023). Electrical Engineering Theses and Dissertations. 68.
https://scholar.smu.edu/engineering_electrical_etds/68
Included in
Other Computer Engineering Commons, Other Electrical and Computer Engineering Commons, Robotics Commons
