Debao Huang

I'm a PhD student in the Geospatial Data Analytics Group at The Ohio State University.

I started in January 2021 and am supervised by Prof. Rongjun Qin. My research interests lie in 3D reconstruction and uncertainty modeling. I am working on multiple projects funded by ONR and IARPA to solve 3D geometry problems and tasks.

Keywords: Structure-from-Motion (SfM), Multi-view Stereo (MVS), Uncertainty Modeling, 3D Reconstruction, Photogrammetry, Remote Sensing.

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News

11/2024

I was honored to be an outstanding reviewer for the 35th British Machine Vision Conference (BMVC 2024).

04/2024

Our new paper of incorporating motion constraints in Bundle Adjustment of Structure-from-Motion for uncalibrated multi-camera systems, got published in ISPRS Journal of Photogrammetry and Remote Sensing.

04/2024

Our new paper of proposing a new scheme to scale up NeRF for large-scale aerial images, got published in The Photogrammetric Record.

06/2023

Our new paper of the preliminary study of uncertainty quantification in MVS, got accepted to ISPRS Geospatial Week 2023.

05/2022

Our new paper of baseline constraint in BA for SfM using uncalibrated multi-camera systems, got accepted to ISPRS Congress 2022.

04/2022

Our new paper of evaluation of PlanetScope images for 3D reconstruction and change detection, got published in GIScience & Remote Sensing Journal.

08/2021

Our new paper of 3D change detection of a building deconstruction event using UAV images, got published in International Journal of Digital Earth.

My Research

BUNDLE ADJUSTMENT WITH MOTION CONSTRAINTS FOR UNCALIBRATED MULTI-CAMERA SYSTEMS AT THE GROUND LEVEL
Debao Huang, Rongjun Qin, Mostafa Elhashash
ISPRS Journal of Photogrammetry and Remote Sensing, 2024
paper | video

This paper derives novel geometric constraints in BA of SfM pipeline that assumes minimal knowns about the uncalibrated multi-camera systems at the ground level. Our proposed constraints are effective in correcting topographical errors (i.e., trajectory drifts) of the reconstruction. It benefits the broader use of photogrammetry with low-cost and non-expert use cases to generate 3D products with improved accuracy.

MULTI-TILING NEURAL RADIANCE FIELD (NERF)—GEOMETRIC ASSESSMENT ON LARGE-SCALE AERIAL DATASETS
Ningli Xu, Rongjun Qin, Debao Huang, Fabio Remondino
The Photogrammetric Record, 2024
paper | video | code

This paper provides multi-camera tiling (MCT) strategy to scale the NeRF on large-scale aerial datasets and a thorough geometry assessment of NeRF.

A CRITICAL ANALYSIS OF INTERNAL RELIABILITY FOR UNCERTAINTY QUANTIFICATION OF DENSE IMAGE MATCHING IN MULTI-VIEW STEREO
Debao Huang, Rongjun Qin
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023
paper

This paper presents preliminary study of metrics in the dense matching and MVS fusion process, to learn heuristic correlation for propagating errors to the final point clouds.

CONSTRAINED BUNDLE ADJUSTMENT FOR STRUCTURE FROM MOTION USING UNCALIBRATED MULTI-CAMERA SYSTEMS
Debao Huang, Mostafa Elhashash, Rongjun Qin
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022
paper

This paper proposes a bundle adjustment (BA) solution for uncalibrated cameras with overlapping views by incorporating a so-called baseline constraint which builds the link between two cameras that are static to each other.

AN EVALUATION OF PLANETSCOPE IMAGES FOR 3D RECONSTRUCTION AND CHANGE DETECTION – EXPERIMENTAL VALIDATIONS WITH CASE STUDIES
Debao Huang, Yang Tang, Rongjun Qin
GIScience & Remote Sensing, 2022
paper | video

This paper comprehensively evaluates the 3D potential of PlanetScope images by performing accuracy analysis for both 3D reconstruction and change detection.

A VOLUMETRIC CHANGE DETECTION FRAMEWORK USING UAV OBLIQUE PHOTOGRAMMETRY – A CASE STUDY OF ULTRA-HIGH-RESOLUTION MONITORING OF PROGRESSIVE BUILDING COLLAPSE
Ningli Xu, Debao Huang, Shuang Song, Xiao Ling, Chris Strasbaugh, Alper Yilmaz, Halil Sezen, Rongjun Qin
International Journal of Digital Earth, 2021
paper | video

This paper presents an unmanned aerial vehicle (UAV) based fine-scale 3D change detection and monitoring of progressive collapse performance of a building during a demolition event.

Software

We've developed a photogrammetry toolkit that accepts a set of images as input, and runs the pipeline from Structure-from-Motion(SfM), Multi-view stereo(MVS), mesh reconstruction to texture mapping. The outputs include estimated camera poses, sparse point clouds, dense point clouds, meshes, and textured meshes. I'm responsible for implementing and maintaining the Structure-from-Motion software. I also design and implement the GUI of the toolkit for better visualization and user interaction. The following video demonstrates an example of running the toolkit GUI on the UAV datasets collected by myself.

Academic Services

I serve as a peer reviewer for:
  • IEEE Transactions on Geoscience and Remote Sensing
  • International Journal of Applied Earth Observation and Geoinformation
  • Photogrammetric Engineering & Remote Sensing
  • British Machine Vision Conference (BMVC 2024) -- Outstanding Reviewer
  • Conference on Neural Information Processing Systems (NeurIPS 2024)
  • Professional Services

    I am a Federal Aviation Administration (FAA) certificated remote pilot, which allows me to collect UAV data for both research and commercial purposes in the US. I have conducted many data collection and surveying tasks that are utilized in our projects and research. The following map shows the flight missions I have conducted on campus.

    © 2024 Debao Huang, last update: 11/13/2024