A Computer Vision Scientist Reacts to the iPhone 15 Announcement

09/18/23 • 42 min

In this episode of Computer Vision Decoded, we are going to dive into our in-house computer vision expert's reaction to the iPhone 15 and iPhone 15 Pro announcement.

We dive into the camera upgrades, decode what a quad sensor means, and even talk about the importance of depth maps.

Episode timeline:

00:00 Intro
02:59 iPhone 15 Overview
05:15 iPhone 15 Main Camera
07:20 Quad Pixel Sensor Explained
15:45 Depth Maps Explained
22:57 iPhone 15 Pro Overview
27:01 iPhone 15 Pro Cameras
32:20 Spatial Video
36:00 A17 Pro Chipset

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

In this episode of Computer Vision Decoded, we are going to dive into our in-house computer vision expert's reaction to the iPhone 15 and iPhone 15 Pro announcement.

We dive into the camera upgrades, decode what a quad sensor means, and even talk about the importance of depth maps.

Episode timeline:

Previous Episode

OpenMVG Decoded: Pierre Moulon's 10 Year Journey Building Open-Source Software

In this episode of Computer Vision Decoded, we are going to dive into Pierre Moulon's 10 years experience building OpenMVG. We also cover the impact of open-source software in the computer vision industry and everything involved in building your own project. There is a lot to learn here!

Our episode guest, Pierre Moulon, is a computer vision research scientist and creator of OpenMVG - a library for computer-vision scientists and targeted for the Multiple View Geometry community.

The episode follow's Pierre's journey building OpenMVG which he wrote about as an article in his GitHub repository.

Explore OpenMVG on GitHub: https://github.com/openMVG/openMVG
Pierre's article on building OpenMVG: https://github.com/openMVG/openMVG/discussions/2165

Episode timeline:

00:00 Intro
01:00 Pierre Moulon's Background
04:40 What is OpenMVG?
08:43 What is the importance of open-source software for the computer vision community?
12:30 What to look for deciding to use an opensource project
16:27 What is Multi View Geometry?
24:24 What was the biggest challenge building OpenMVG?
31:00 How do you grow a community around an open-source project
38:09 Choosing a licensing model for your open-source project
43:07 Funding and sponsorship for your open-source project
46:46 Building an open-source project for your resume
49:53 How to get started with OpenMVG

Contact:
Follow Pierre Moulon on LinkedIn: https://www.linkedin.com/in/pierre-moulon/
Follow Jared Heinly on Twitter: https://twitter.com/JaredHeinly
Follow Jonathan Stephens on Twitter at: https://twitter.com/jonstephens85

Next Episode

What's New in 2025 for Computer Vision?

After an 18 month hiatus, we are back! In this episode of Computer Vision Decoded, hosts Jonathan Stephens and Jared Heinly discuss the latest advancements in computer vision technology, personal updates, and insights from the industry. They explore topics such as real-time 3D reconstruction, computer vision research, SLAM, event cameras, and the impact of generative AI on robotics. The conversation highlights the importance of merging traditional techniques with modern machine learning approaches to solve real-world problems effectively.

Chapters

00:00 Intro & Personal Updates
04:36 Real-Time 3D Reconstruction on iPhones
09:40 Advancements in SfM
14:56 Event Cameras
17:39 Neural Networks in 3D Reconstruction
26:30 SLAM and Machine Learning Innovation
29:48 Applications of SLAM in Robotics
34:19 NVIDIA's Cosmos and Physical AI
40:18 Generative AI for Real-World Applications
43:50 The Future of Gaussian Splatting and 3D Reconstruction