3D Reconstruction in the Wild
from Computer Vision Decoded Hosted by EveryPoint
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 Project: Reconstructing the World in Six Days Video: Reconstructing the world in Six Days Follow Jared Heinly on Twitter Follow Jonathan Stephens on Twitter 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
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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.
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