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Learner Reviews & Feedback for Visual Perception for Self-Driving Cars by University of Toronto

4.7
stars
407 ratings
56 reviews

About the Course

Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the end of this course, you will be able to work with the pinhole camera model, perform intrinsic and extrinsic camera calibration, detect, describe and match image features and design your own convolutional neural networks. You'll apply these methods to visual odometry, object detection and tracking, and semantic segmentation for drivable surface estimation. These techniques represent the main building blocks of the perception system for self-driving cars. For the final project in this course, you will develop algorithms that identify bounding boxes for objects in the scene, and define the boundaries of the drivable surface. You'll work with synthetic and real image data, and evaluate your performance on a realistic dataset. This is an advanced course, intended for learners with a background in computer vision and deep learning. To succeed in this course, you should have programming experience in Python 3.0, and familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses)....

Top reviews

AQ
Feb 27, 2020

The course has proved to another milestone in furthering my understanding of robotics, computer vision, machine learning and autonomous driving vehicles.

BS
Nov 7, 2020

Really really great course. I would like to work with Prof.Waslander at any project. I will advise this course to anyone interested. Thanks Coursera!

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51 - 55 of 55 Reviews for Visual Perception for Self-Driving Cars

By Marco

Jul 31, 2020

Please make sure the syntax is consistent. One thing I remember was a c_u instead of u_c. I feel sometimes that the explanation in the assignments can be more specific as it is otherwise a lot of guessing or extra learning.

By Sen Y

Jan 12, 2020

I feel disappointed. Programming assignments are neither for 2D object detection nor for semantic segmentation.

By Levente K

Mar 25, 2019

Good intro for those with not much experience w/ image processing/computer vision w.r.t. autonomous driving.

By Omkar K

Jun 30, 2020

The range of topics was good but it would have been better if they were explained more.

By Yan X

Dec 23, 2020

The content is good, project can be more complicated. One thing I have to complain is the course is lacking support. Specially the common problems about course content and technical issues are long waiting for answers. This will make learners feel really frustrated.