Abstract: Systems, methods, and computer readable media to track and estimate the accuracy of a visual inertial odometry (VIO) system. Various embodiments are able to receive one or more VIO feature measurements associated with a set of image frames from a VIO system and generate a plurality of feature models to estimate health values for the VIO system. The various embodiments determine a plurality of feature health values with the feature models based on the VIO feature measurements and compare the feature health values with ground truth health scores associated with the set of image frames to determine one or more errors. The feature model parameters are updated based on the comparison with the feature health values with ground truth health scores.

Abstract: A method includes obtaining training samples that include images that depict objects and annotations of annotated key point locations for the objects. The method also includes training a machine learning model to determine estimated key point locations for the objects and key point uncertainty values for the estimated key point locations by minimizing a loss function that is based in part on a key point localization loss value that represents a difference between the annotated key point locations and the estimated key point locations values and is weighted by the key point uncertainty values.

Abstract: Systems, methods, and computer readable media to track and estimate the accuracy of a visual inertial odometry (VIO) system. Various embodiments are able to receive one or more VIO feature measurements associated with a set of image frames from a VIO system and generate a plurality of feature models to estimate health values for the VIO system. The various embodiments determine a plurality of feature health values with the feature models based on the VIO feature measurements and compare the feature health values with ground truth health scores associated with the set of image frames to determine one or more errors. The feature model parameters are updated based on the comparison with the feature health values with ground truth health scores.