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Description

In this episode of Computer Vision Decoded, Jonathan Stephens and Jared Heinly explore the concept of depth maps in computer vision. They discuss the basics of depth and depth maps, their applications in smartphones, and the various types of depth maps. The conversation delves into the role of depth maps in photogrammetry and 3D reconstruction, as well as future trends in depth sensing and machine learning. The episode highlights the importance of depth maps in enhancing photography, gaming, and autonomous systems.

Key Takeaways:


Episode Chapters
00:00 Introduction to Depth Maps

00:13 Understanding Depth in Computer Vision

06:52 Applications of Depth Maps in Photography

07:53 Types of Depth Maps Created by Smartphones

08:31 Depth Measurement Techniques

16:00 Machine Learning and Depth Estimation

19:18 Absolute vs Relative Depth Maps

23:14 Disparity Maps and Depth Ordering

26:53 Depth Maps in Graphics and Gaming

31:24 Depth Maps in Photogrammetry

34:12 Utilizing Depth Maps in 3D Reconstruction

37:51 Sensor Fusion and SLAM Technologies

41:31 Future Trends in Depth Sensing

46:37 Innovations in Computational Photography

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. Learn more at https://www.everypoint.io