Blob Feature Extraction for Event Detection Cameras
Date of Award
2020
Degree Name
M.S. in Electrical Engineering
Department
Department of Electrical and Computer Engineering
Advisor/Chair
Advisor: Keigo Hirakawa
Abstract
Neuromorphic (a.k.a. event detection) cameras emerged out of biologically inspired visual perception. A key component of neuromorphic cameras is the dynamic vision sensor or DVS, which generates an asynchronous data stream reporting temporal log-intensity changes (or "events") of the pixel-sized photodiodes. In this thesis a novel blob feature extraction technique for neuromorphic cameras is proposed. Using asynchronous 3D distance transform, we are able to track a blob, describe its size/shape/orientation, efficiently match the feature descriptors, and perform image correspondence across multiple neuromorphic cameras.
Keywords
Electrical Engineering
Rights Statement
Copyright © 2020, author
Recommended Citation
Raffoul, Joseph Naim, "Blob Feature Extraction for Event Detection Cameras" (2020). Graduate Theses and Dissertations. 6708.
https://ecommons.udayton.edu/graduate_theses/6708
