So far, we have seen all the concepts related to parallel programming using CUDA and how it can leverage the GPU for acceleration. From this chapter on, we will try to use the concept of parallel programming in CUDA for computer vision applications. Though we have worked on matrices, we have not worked on actual images. Basically, working on images is similar to manipulation of two-dimensional matrices. We will not develop the entire code from scratch for computer vision applications in CUDA, but we will use the popular computer vision library that is called OpenCV. Though this book assumes that the reader has some familiarity with working with OpenCV, this chapter revises the concepts of using OpenCV in C++. This chapter describes the installation of the OpenCV library with CUDA support on Windows and Ubuntu. Then it describes how...
United States
Great Britain
India
Germany
France
Canada
Russia
Spain
Brazil
Australia
Singapore
Hungary
Philippines
Mexico
Thailand
Ukraine
Luxembourg
Estonia
Lithuania
Norway
Chile
South Korea
Ecuador
Colombia
Taiwan
Switzerland
Indonesia
Cyprus
Denmark
Finland
Poland
Malta
Czechia
New Zealand
Austria
Turkey
Sweden
Italy
Egypt
Belgium
Portugal
Slovenia
Ireland
Romania
Greece
Argentina
Malaysia
South Africa
Netherlands
Bulgaria
Latvia
Japan
Slovakia