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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

2D scale space relation


Another large advantage that we can exploit in industrial cases is the fact that many of these setups have a fixed camera position. This is interesting when the objects that need to be detected follow a fixed ground plane, like in the case of pedestrians or objects passing by on a conveyor belt. If these conditions exist, then there is actually a possibility to model the scale of an object at each position in the image. This yields two possible advantages:

  • First of all, you can use this knowledge to effectively reduce the number of false positive detections while still keeping your certainty threshold low enough so that low certainty and good detection still stick around. This can be done in some sort of post-processing step after the object detection phase.

  • Secondly, this knowledge can be used to effectively reduce the detection time and search space for object candidates inside the image pyramid.

Let's start by focusing on the following case, illustrated in the following...

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