Tracking Objects in Video with Particle Filters
Offered By: Coursera Project Network via Coursera
Course Description
Overview
In this one hour long project-based course, you will tackle a real-world computer vision problem. We will be locating and tracking a target in a video shot with a digital camera. We will encounter some of the classic challenges that make computer vision difficult: noisy sensor data, objects that change shape, and occlusion (object hidden from view).
We will tackle these challenges with an artificial intelligence technique called a particle filter.
By the end of this project, you will have coded a particle filter from scratch using Python and numpy.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Syllabus
- Project Overview
- In this one hour long project-based course, you will tackle a real-world computer vision problem. We will be locating and tracking a target in a video shot with a digital camera. We will encounter some of the classic challenges that make computer vision difficult: noisy sensor data, objects that change shape, and occlusion (object hidden from view). We will tackle these challenges with an artificial intelligence technique called a particle filter.
Taught by
Daniel Romaniuk
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