Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
OpenCV 3 Blueprints

You're reading from   OpenCV 3 Blueprints Expand your knowledge of computer vision by building amazing projects with OpenCV 3

Arrow left icon
Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784399757
Length 382 pages
Edition 1st Edition
Tools
Arrow right icon
Toc

Table of Contents (9) Chapters Close

Preface 1. Getting the Most out of Your Camera System FREE CHAPTER 2. Photographing Nature and Wildlife with an Automated Camera 3. Recognizing Facial Expressions with Machine Learning 4. Panoramic Image Stitching Application Using Android Studio and NDK 5. Generic Object Detection for Industrial Applications 6. Efficient Person Identification Using Biometric Properties 7. Gyroscopic Video Stabilization Index

Obtaining rotation invariance object detection


A large downside to the current OpenCV cascade classifier implementation is that it only supports multiscale single rotation object detection. Many industrial applications that could actually use object detection do not know the orientation of the object beforehand and thus rotation invariant multiscale object detection would be much more interesting. Therefore, I will guide you through some techniques for applying multiscale rotation invariant object detection, by simply using the provided functionality in OpenCV.

Note

OpenCV 3 also provides other techniques that are able to perform multiscale rotation invariant object categorization like the Bag of Visual Words approach. A good tutorial on this technique can be found at https://gilscvblog.wordpress.com/2013/08/23/bag-of-words-models-for-visual-categorization/.

There are three main ideas when trying to achieve rotation invariant object detection:

  • Train a single object model with all possible orientations...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime