Machine Learning Computer Vision Applications for Spatial AI Object
Recognition in Orange County, California
- URL: http://arxiv.org/abs/2303.07560v1
- Date: Tue, 14 Mar 2023 00:57:11 GMT
- Title: Machine Learning Computer Vision Applications for Spatial AI Object
Recognition in Orange County, California
- Authors: Kostas Alexandridis
- Abstract summary: We provide an integrated and systematic automation approach to spatial object recognition and positional detection using AI machine learning and computer vision algorithms for Orange County, California.
We describe a comprehensive methodology for multi-sensor, high-resolution field data acquisition, along with post-field processing and pre-analysis processing tasks.
We provide examples of application processing more than 800 thousand cardinal directions in photosphere images across two areas in Orange County, and present detection results for stop-sign and fire hydrant object recognition.
- Score: 4.089055556130725
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: We provide an integrated and systematic automation approach to spatial object
recognition and positional detection using AI machine learning and computer
vision algorithms for Orange County, California. We describe a comprehensive
methodology for multi-sensor, high-resolution field data acquisition, along
with post-field processing and pre-analysis processing tasks. We developed a
series of algorithmic formulations and workflows that integrate convolutional
deep neural network learning with detected object positioning estimation in
360{\deg} equirectancular photosphere imagery. We provide examples of
application processing more than 800 thousand cardinal directions in
photosphere images across two areas in Orange County, and present detection
results for stop-sign and fire hydrant object recognition. We discuss the
efficiency and effectiveness of our approach, along with broader inferences
related to the performance and implications of this approach for future
technological innovations, including automation of spatial data and public
asset inventories, and near real-time AI field data systems.
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