From 2D to 3D: 4 Ways to Make a 3D Reconstruction from Imagery

https://is1-ssl.mzstatic.com/image/thumb/Podcasts211/v4/a0/48/74/a048745c-0ce8-e9b0-f8fb-fd015479f495/mza_14678048729076270743.jpg/600x600bb.jpg

Computer Vision Decoded

EveryPoint

18 episodes

4 months ago

A tidal wave of computer vision innovation is quickly having an impact on everyone's lives, but not everyone has the time to sit down and read through a bunch of news articles and learn what it means for them. In Computer Vision Decoded, we sit down with Jared Heinly, the Chief Scientist at EveryPoint, to discuss topics in today’s quickly evolving world of computer vision and decode what they mean for you. If you want to be sure you understand everything happening in the world of computer vision, don't miss an episode!

Technology

Science

RSS

All content for Computer Vision Decoded is the property of EveryPoint and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.

Technology

Science

From 2D to 3D: 4 Ways to Make a 3D Reconstruction from Imagery

Computer Vision Decoded

54 minutes

2 years ago

From 2D to 3D: 4 Ways to Make a 3D Reconstruction from Imagery

In this episode of Computer Vision Decoded, we are going to dive into 4 different ways to 3D reconstruct a scene with images. Our cohost Jared Heinly, a PhD in the computer science specializing in 3D reconstruction from images, will dive into the 4 distinct strategies and discuss the pros and cons of each.

Links to content shared in this episode:

Live SLAM to measure a stockpile with SR Measure: https://srmeasure.com/professional

Jared's notes on the iPhone LiDAR and SLAM: https://everypoint.medium.com/everypoint-gets-hands-on-with-apples-new-lidar-sensor-44eeb38db579

How to capture images for 3D reconstruction: https://youtu.be/AQfRdr_gZ8g

00:00 Intro
01:30 3D Reconstruction from Video
13:48 3D Reconstruction from Images
28:05 3D Reconstruction from Stereo Pairs
38:43 3D Reconstruction from SLAM

Follow Jared Heinly
Twitter: https://twitter.com/JaredHeinly
LinkedIn https://www.linkedin.com/in/jheinly/

Follow Jonathan Stephens
Twitter: https://twitter.com/jonstephens85
LinkedIn: https://www.linkedin.com/in/jonathanstephens/

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