Book Image

Learning OpenCV 3 Computer Vision with Python (Update)

Book Image

Learning OpenCV 3 Computer Vision with Python (Update)

Overview of this book

Table of Contents (16 chapters)
Learning OpenCV 3 Computer Vision with Python Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
6
Retrieving Images and Searching Using Image Descriptors
Index

Object detection and recognition techniques


We made a distinction in Chapter 5, Detecting and Recognizing Faces, which we'll reiterate for clarity: detecting an object is the ability of a program to determine if a certain region of an image contains an unidentified object, and recognizing is the ability of a program to identify this object. Recognizing normally only occurs in areas of interest where an object has been detected, for example, we have attempted to recognize faces on the areas of an image that contained a face in the first place.

When it comes to recognizing and detecting objects, there are a number of techniques used in computer vision, which we'll be examining:

  • Histogram of Oriented Gradients

  • Image pyramids

  • Sliding windows

Unlike feature detection algorithms, these are not mutually exclusive techniques, rather, they are complimentary. You can perform a Histogram of Oriented Gradients (HOG) while applying the sliding windows technique.

So, let's take a look at HOG first and understand...