Search Results for author: Gordon Christie

Found 11 papers, 5 papers with code

Single View Geocentric Pose in the Wild

1 code implementation18 May 2021 Gordon Christie, Kevin Foster, Shea Hagstrom, Gregory D. Hager, Myron Z. Brown

Current methods for Earth observation tasks such as semantic mapping, map alignment, and change detection rely on near-nadir images; however, often the first available images in response to dynamic world events such as natural disasters are oblique.

Change Detection Earth Observation

Towards Indirect Top-Down Road Transport Emissions Estimation

no code implementations16 Mar 2021 Ryan Mukherjee, Derek Rollend, Gordon Christie, Armin Hadzic, Sally Matson, Anshu Saksena, Marisa Hughes

In this work, we develop machine learning models that use satellite imagery to perform indirect top-down estimation of road transport emissions.

Learning Geocentric Object Pose in Oblique Monocular Images

1 code implementation CVPR 2020 Gordon Christie, Rodrigo Rene Rai Munoz Abujder, Kevin Foster, Shea Hagstrom, Gregory D. Hager, Myron Z. Brown

An object's geocentric pose, defined as the height above ground and orientation with respect to gravity, is a powerful representation of real-world structure for object detection, segmentation, and localization tasks using RGBD images.

Earth Observation Object +4

Estimating Displaced Populations from Overhead

1 code implementation25 Jun 2020 Armin Hadzic, Gordon Christie, Jeffrey Freeman, Amber Dismer, Stevan Bullard, Ashley Greiner, Nathan Jacobs, Ryan Mukherjee

We introduce a deep learning approach to perform fine-grained population estimation for displacement camps using high-resolution overhead imagery.

Humanitarian

Semantic Stereo for Incidental Satellite Images

1 code implementation21 Nov 2018 Marc Bosch, Kevin Foster, Gordon Christie, Sean Wang, Gregory D. Hager, Myron Brown

The increasingly common use of incidental satellite images for stereo reconstruction versus rigidly tasked binocular or trinocular coincident collection is helping to enable timely global-scale 3D mapping; however, reliable stereo correspondence from multi-date image pairs remains very challenging due to seasonal appearance differences and scene change.

3D Reconstruction Scene Segmentation +1

Functional Map of the World

7 code implementations CVPR 2018 Gordon Christie, Neil Fendley, James Wilson, Ryan Mukherjee

We present an analysis of the dataset along with baseline approaches that reason about metadata and temporal views.

Temporal Sequences

Radiation Search Operations using Scene Understanding with Autonomous UAV and UGV

no code implementations31 Aug 2016 Gordon Christie, Adam Shoemaker, Kevin Kochersberger, Pratap Tokekar, Lance McLean, Alexander Leonessa

Autonomously searching for hazardous radiation sources requires the ability of the aerial and ground systems to understand the scene they are scouting.

Scene Segmentation Scene Understanding +1

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