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  • Book
  • © 2019

Learn Computer Vision Using OpenCV

With Deep Learning CNNs and RNNs

Apress

Authors:

(view affiliations)
  • Helps readers get a jump start to computer vision implementations

  • Offers use-case driven implementation for computer vision with focused learning on OpenCV and Python libraries

  • Helps create deep learning models with CNN and RNN, and explains how these cutting-edge deep learning architectures work

Buying options

eBook
USD 34.99
Price excludes VAT (USA)
  • ISBN: 978-1-4842-4261-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD 44.99
Price excludes VAT (USA)

This is a preview of subscription content, access via your institution.

Table of contents (6 chapters)

  1. Front Matter

    Pages i-xx
  2. Artificial Intelligence and Computer Vision

    • Sunila Gollapudi
    Pages 1-29
  3. OpenCV with Python

    • Sunila Gollapudi
    Pages 31-50
  4. Deep Learning for Computer Vision

    • Sunila Gollapudi
    Pages 51-69
  5. Image Manipulation and Segmentation

    • Sunila Gollapudi
    Pages 71-96
  6. Object Detection and Recognition

    • Sunila Gollapudi
    Pages 97-117
  7. Motion Analysis and Object Tracking

    • Sunila Gollapudi
    Pages 119-145
  8. Back Matter

    Pages 147-151

About this book

Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. 

The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you’ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision.

After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work.

You will:
  • Understand what computer vision is, and its overall application in intelligent automation systems
  • Discover the deep learning techniques required to build computer vision applications
  • Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy
  • Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis

Keywords

  • Computer Vision
  • Open CV
  • Python
  • Deep Learning
  • Artificial intelligence
  • Image Segmentation
  • Object Detection

Authors and Affiliations

  • Hyderabad, India

    Sunila Gollapudi

About the author

Sunila Gollapudi has over 17 years of experience in developing, designing and architecting data-driven solutions with a focus on the banking and financial services sector. She is currently working at  Broadridge, India as vice president. She's played various roles as chief architect, big data and AI evangelist, and mentor.

She has been a speaker at various conferences and meetups on Java and big data technologies. Her current big data and data science expertise includes Hadoop, Greenplum, MarkLogic, GemFire, ElasticSearch, Apache Spark, Splunk, R, Julia, Python (scikit-learn), Weka, MADlib, Apache Mahout, and advanced analytics techniques such as deep learning, computer vision, reinforcement, and ensemble learning.

Bibliographic Information

Buying options

eBook
USD 34.99
Price excludes VAT (USA)
  • ISBN: 978-1-4842-4261-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD 44.99
Price excludes VAT (USA)