Tracking Objects in Video with Particle Filters

Offered By
Coursera Project Network
In this Guided Project, you will:

C​ode a particle filter from scratch in Python and use it to track a target in a real-world video.

Clock1 hour
AdvancedAdvanced
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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.

Skills you will develop

Particle FilterOpencvArtificial Intelligence (AI)Python ProgrammingNumpy

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Load video frames

  2. Display video frames

  3. Initialize a particle filter

  4. Compute errors

  5. Compute weights and resample

  6. Apply noise

  7. Optimize the particle filter

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

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