How Do Self-Driving Cars Really 'See'?

Apr 06, 2024

Did you know that self-driving cars 'see' the world differently than we do?

It's an intricate dance of computer algorithms and sensors that makes these vehicles so smart.

After diving into control systems during my academic years, I ventured into the fascinating but perplexing world of image processing.

To be honest, I was seriously lost.

Back in undergrad, we barely scratched the surface of coding, and computer vision wasn't nearly as advanced as it is today.

So, I turned to my supervisor for advice, who simply said, "Start with something simple like detecting circles. Once you've got that down, you can move on to more advance models."

And that's exactly what I did. I printed A4 pages with huge black circles, stuck them on the back of my car, and used basic techniques like thresholding, and shape detection.

By knowing the circle's size, I could calculate the distance to the car ahead.

It wasn't ideal, but HEY, I was learning okay 🤣!

Eventually, I transitioned from these fiducial markers to pattern matching, using LabVIEW—a far cry from the best software for this but good enough for learning.

Today, computer vision has been revolutionized by deep learning and Convolutional Neural Networks (CNNs). We're no longer confined to basic shapes and thresholding techniques.

With algorithms like YOLOv8,v9 & YOLO-NAS, amongst many others, we can detect cars, pedestrians, and even the minutest of road details with incredible precision and accuracy.

And here's the kicker: In Module 4 of the Self-Driving Car (SDC) Specialization Pro Course, you won't be lost detecting circles like I was.

You'll have a guiding hand to walk you through state-of-the-art techniques that are at the forefront of today's self-driving car technology.

You'll learn to harness powerful algorithms, engage with complex neural networks, and apply these skills in real-world scenarios.

Module 4: A Deep Dive into Visual Perception 🎥

Introduction to Computer Vision: Learn the foundational principles.
2D & 3D Object Detection & Tracking: Understand how cars see and interpret objects.
Semantic Segmentation: Discover how cars differentiate between roads, pedestrians, and other vehicles.
Tesla HydraNets: Get to know this advanced neural network architecture for complex tasks.
Real-Time Vision Depth Perception: Master the techniques used for real-time depth perception.

By the end of this module, you'll know exactly how a self-driving car 'sees' the world, and you'll have the skills to prove it.

Join the Self-Driving Car Mastery Course through Augmented AI University

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