Dense depth estimation of image data

Systems, devices, and methods are described for generating dense depth estimates, and confidence values associated with such depth estimates, from image data. A machine learning algorithm can be trained using image data and associated depth values captured by one or more LIDAR sensors providing a gr...

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Main Authors Mousavian, Arsalan, Philbin, James William Vaisey
Format Patent
LanguageEnglish
Published 19.07.2022
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Abstract Systems, devices, and methods are described for generating dense depth estimates, and confidence values associated with such depth estimates, from image data. A machine learning algorithm can be trained using image data and associated depth values captured by one or more LIDAR sensors providing a ground truth. When the algorithm is deployed in a machine vision system, image data and/or depth data can be used to determine dense depth estimates for all pixels of the image data, as well as confidence values for each depth estimate. Such confidence values may be indicative of how confident the machine learned algorithm is of the associated depth estimate.
AbstractList Systems, devices, and methods are described for generating dense depth estimates, and confidence values associated with such depth estimates, from image data. A machine learning algorithm can be trained using image data and associated depth values captured by one or more LIDAR sensors providing a ground truth. When the algorithm is deployed in a machine vision system, image data and/or depth data can be used to determine dense depth estimates for all pixels of the image data, as well as confidence values for each depth estimate. Such confidence values may be indicative of how confident the machine learned algorithm is of the associated depth estimate.
Author Philbin, James William Vaisey
Mousavian, Arsalan
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Snippet Systems, devices, and methods are described for generating dense depth estimates, and confidence values associated with such depth estimates, from image data....
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COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
Title Dense depth estimation of image data
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