Vision Models And Applications to Image And Video Processing

Apply computer vision and machine learning concepts in developing business and industrial applications ​using a practical, step-by-step approach.

Grasp the concepts of OpenCV 4 to build powerful machine learning systems and computer vision applications with OpenCV 4

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars.

Visual quality assessment is an interdisciplinary topic that links image/video processing, psychology and physiology. Many engineers are familiar with the image/video processing; transmission networks side of things but not with the perceptual aspects pertaining to quality. Digital Video Quality first introduces the concepts of human vision and visual quality. Based on these, specific video quality metrics are developed and their design is presented. These metrics are then evaluated and used in a number of applications, including image/video compression, transmission and watermarking.

Learn to implement popular CV algorithms with OpenCV python library

The book presents an overview of 3-D cinematography, the science and technology of generating 3-D models of dynamic scenes from multiple cameras at video frame rates. The book covers recent developments in computer vision and computer graphics that have made 3-D cinematography possible, and reviews the challenges and open issues that need to be addressed in future work.