Title
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
