OpenCV Computer Vision Application Programming [Video], Sebastian Montabone, [PACKT video]

The video course OpenCV Computer Vision Application Programming is a series of screencasts covering different aspects of computer vision which shows you how to create computer vision applications using OpenCV.

Video course sections:

  • Getting Started with OpenCV. Get to know OpenCV and learn how to install it.
  • OpenCV Basics.Learn about the basics of OpenCV, the different programming interfaces it offers as well as an introduction to the Python, C, and C++ interfaces.
  • Image Processing. Learn some of the basics of image processing such as blurring an image, understanding image morphology, geometric transforms, and image histograms.
  • Segmenting Images and Obtaining Interesting Points. Apply different algorithms to cluster data, segment images, as well as find and match interesting points in an image.
  • Computational Photography. Create panoramas, remove unwanted objects from photos, enhance low light photographs, and work with High Dynamic Range (HDR) images.
  • Recognizing Objects. Detect different shapes, faces, people, and learn how to train a detector to detect custom objects and to recognize faces.
  • Calibration and Stereo Images. Learn how to calibrate cameras, remove distortion from images, change the 3D perspective of photographs, and work with stereo images to represent depth information.

This video course can be purchased from Packt

Viewers only need to have basic programming experience to follow the course and start adding computer vision capabilities to their applications. Since each example in the course is independent from the others, viewers can pick and choose the ones that apply to their needs as a starting point for their applications.

The author of this video course is Sebastian Montabone, a computer engineer with both professional and personal experience with OpenCV. He has written articles about OpenCV on his blog and recently was a technical editor of the book Mastering OpenCV with Practical Computer Vision Projects.