Velocity Moments: Capturing the Dynamics: Insights into Computer Vision
About this ebook
In the field of computer vision, velocity moments are weighted averages of the intensities of pixels in a sequence of images, similar to image moments but in addition to describing an object's shape also describe its motion through the sequence of images. Velocity moments can be used to aid automated identification of a shape in an image when information about the motion is significant in its description. There are currently two established versions of velocity moments: Cartesian and Zernike.
How you will benefit
(I) Insights, and validations about the following topics:
Chapter 1: Velocity Moments
Chapter 2: Navier-Stokes equations
Chapter 3: Mean squared error
Chapter 4: Rigid rotor
Chapter 5: Directional statistics
Chapter 6: Circular distribution
Chapter 7: Von Mises distribution
Chapter 8: Rice distribution
Chapter 9: Wrapped normal distribution
Chapter 10: Variance gamma process
(II) Answering the public top questions about velocity moments.
(III) Real world examples for the usage of velocity moments in many fields.
Who this book is for
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Velocity Moments.
