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OpenCV 3 Blueprints

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

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784399757
Length 382 pages
Edition 1st Edition
Tools
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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

Stabilization with images


Video stabilization with images alone seems like the first logical step. Indeed, initial research on stabilizing video captured by cameras was based on using information readily available from the camera sensors to understand how they move image by image.

The idea is to find keypoints in an image sequence to understand how they move image by image. Keypoints are pixel locations on an image that match these criteria:

  • Keypoints should be easily recognizable and distinguishable from each other. Corners of objects are good keypoints while a point on a blank wall is not.

  • It should be possible to track keypoints across multiple images to calculate motion. You should be able to tell exactly where the keypoint has moved from one frame to another.

  • For performance, identifying these keypoints should be fast and memory-efficient. This is usually a bottleneck on low memory and low power devices.

Research with these criteria led to several unique approaches like including some famous...

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