3D Reconstruction in the Wild - Computer Vision Decoded Ep. 3

In this episode of Computer Vision Decoded, we sit down with Jared Heinly, Chief Scientist at EveryPoint, to discuss 3D reconstruction in the wild. What does “in the wild” mean? This means 3D reconstructing objects and scenes in non-controlled environments where you may have limitations with lighting, access, reflective surfaces, etc.

00:00 Intro
01:30: What are Duplicate Scene Structures and How to Avoid Them
14:30: How Jared used 100 million crowdsourced photos to 3d reconstruct 12,903 landmarks
27:10: The benefits of capturing video for 3D reconstruction
31:30: The benefits of using a drone to capture stills for 3D reconstruction
34:20: Considerations for using installed cameras for 3d reconstruction
38:30: How to work with sun issues
44:25: Determining how far from the object you should be when capturing images
50:35: How to capture objects with reflective surfaces
53:40: How work around scene obstructions
57:20: What cameras you should use

Jared Heinly’s Academic Papers and Projects

Paper: Correcting the Duplicate Scene Structure In Sparse 3D Reconstruction - https://www.cs.unc.edu/~jheinly/publi...

Project: Reconstructing the World in Six Days - https://www.cs.unc.edu/~jheinly/recon...

Video: Reconstructing the world in Six Days:    • Reconstructing the World* in Six Days *(As...  

Follow Jared Heinly on Twitter:   / jaredheinly  
Follow Jonathan Stephens on Twitter at:   / jonstephens85  

This episode is brought to you by EveryPoint. Learn more about how EveryPoint is building an infinitely scalable data collection and processing platform for the next generation of spatial computing applications and services: https://www.everypoint.io