Librería Portfolio

Book Description

OpenCV is a native cross platform C++ Library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. OpenCV has C++/C, Python, and Java interfaces with support for Windows, Linux, Mac, iOS, and Android. Developers using OpenCV build applications to process visual data; this can include live streaming data from a device like a camera, such as photographs or videos. OpenCV offers extensive libraries with over 500 functions

This book demonstrates how to develop a series of intermediate to advanced projects using OpenCV and Python, rather than teaching the core concepts of OpenCV in theoretical lessons. Instead, the working projects developed in this book teach the reader how to apply their theoretical knowledge to topics such as image manipulation, augmented reality, object tracking, 3D scene reconstruction, statistical learning, and object categorization.

By the end of this book, readers will be OpenCV experts whose newly gained experience allows them to develop their own advanced computer vision applications.

Table of Contents

1: FUN WITH FILTERS
2: HAND GESTURE RECOGNITION USING A KINECT DEPTH SENSOR
3: FINDING OBJECTS VIA FEATURE MATCHING AND PERSPECTIVE TRANSFORMS
4: 3D SCENE RECONSTRUCTION USING STRUCTURE FROM MOTION
5: TRACKING VISUALLY SALIENT OBJECTS
6: LEARNING TO RECOGNIZE TRAFFIC SIGNS
7: LEARNING TO RECOGNIZE EMOTIONS ON FACES
What You Will Learn

Generate real-time visual effects using different filters and image manipulation techniques such as dodging and burning
Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor
Learn feature extraction and feature matching for tracking arbitrary objects of interest
Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques
Track visually salient objects by searching for and focusing on important regions of an image
Detect faces using a cascade classifier and recognize emotional expressions in human faces using multi-layer peceptrons (MLPs)
Recognize street signs using a multi-class adaptation of support vector machines (SVMs)
Strengthen your OpenCV2 skills and learn how to use new OpenCV3 features