Images can be described as visual representations or likeness of something (person or
object) which can be reproduced or captured, eg a hand drawing, photographic material …

This work focuses on a slice through the field-Computer Vision Metrics–from the view of
feature description metrics, or how to describe, compute and design the macro-features and …

Many algorithms for computer vision rely on locating interest points, or keypoints in each
image, and calculating a feature description from the pixel region surrounding the interest …

The deep learning-based image inpainting models discussed in this review are critical
image processing techniques for filling in missing or removed regions in static planar …

In one embodiment of the invention, an apparatus is disclosed including an image sensor, a
color filter array, and an image processor. The image sensor has an active area with a matrix …

Scott Krig Textbook Edition Survey, Taxonomy and Analysis of Computer Vision, Visual
Neuroscience, and Deep Learning Page 1 Computer Vision Metrics Scott Krig Textbook Edition …

In one embodiment of the invention, an apparatus is disclosed including an image sensor, a
color filter array, and an image processor. The image sensor has an active area with a matrix …

Image quality is a well understood concept for human viewing applications, particularly in
the multimedia space, but increasingly in an automotive context as well. The rise in …

Emerging sensor designs increasingly rely on novel color filter arrays (CFAs) to sample the
incident spectrum in unconventional ways. In particular, capturing a near-infrared (NIR) …

This chapter discusses several topics pertaining to ground truth data, the basis for computer
vision metric analysis. We look at examples to illustrate the importance of ground truth data …