Introduction to Computer Vision - Code Heroku
- 1. Please turn off your webcam. If you are joining from Mobile device make sure you click on Join via Device Audio We are waiting for other participants to join. Thank you for your patience!
- 2. Mihir Thakkar Founder and Instructor hello@codeheroku.com
- 3. SESSION OBJECTIVES ● What is Computer Vision? ● Why you should learn it? ● How you should go about learning it? ● Basics of Image Processing ● Try simple algorithms using Python and OpenCV
- 4. Let’s Do A Visual Rapid Fire
- 10. Computer Vision ● What’s in the scene? ● Where? Where is it? ● How to manipulate the object or move around the scene. (Environmental understanding for robotic navigation or self-driving vehicles)
- 11. Let’s Look At Some Applications
- 12. Challenges in building a Computer Vision System ● Real world data is noisy ● Scale / Orientation / Lighting variations ● There is always a lack of annotated / meaningful data
- 13. Images And Pixels (0,0) x y
- 14. Color Images
- 15. How Do I Learn Computer Vision? Image / Video Capture Sampling, Quantization, etc.. Pre-processing Filtering, Thresholding etc.. Feature Extraction Contour Detection, Edge Detection, PCA etc.. ML Model Supervised /Unsupervised Learning Real World Manipulation Localization, Object Tracking Path Planning
- 16. Thresholding
- 17. Histogram of a Sample Image
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