Mohammed E Salem, 71Los Angeles, CA

2019006, Feb 28, 2019

Jul 6, 2018

16/029126

- Princeton NJ, US
Mohammed E.F. Salem - Hyattsville MD, US
Muhammad Zeeshan Zia - San Jose CA, US
Paul Vernaza - Sunnyvale CA, US
Manmohan Chandraker - Santa Clara CA, US

G06T 17/05
G06K 9/62
G06K 9/46
G06K 9/66
G06N 3/08

Systems and methods for correspondence estimation and flexible ground modeling include communicating two-dimensional (2D) images of an environment to a correspondence estimation module, including a first image and a second image captured by an image capturing device. First features, including geometric features and semantic features, are hierarchically extract from the first image with a first convolutional neural network (CNN) according to activation map weights, and second features, including geometric features and semantic features, are hierarchically extracted from the second image with a second CNN according to the activation map weights. Correspondences between the first features and the second features are estimated, including hierarchical fusing of geometric correspondences and semantic correspondences. A 3-dimensional (3D) model of a terrain is estimated using the estimated correspondences belonging to the terrain surface. Relative locations of elements and objects in the environment are determined according to the 3D model of the terrain. A user is notified of the relative locations.