WHAT IS COMPUTER VISION?
Introduction to the Field of Computer Vision
Originated from the large field of artificial intelligence, computer vision is
concerned with the study of enabling machines to perform visual tasks.
The inputs to machines are images or video sequences, captured through a
live camera feed. These tasks range from low-level de-nosing and filtering,
to mid-level region growing or image/video segmentation (i.e., the operation
of grouping image pixels into semantically uniform entities), and
eventually to high-level detection or recognition (e.g., recognizing objects
or faces in images). The old Chinese proverb, “A picture is worth a thousand
words,” best summarizes the challenges and opportunities of this
field. While it is beneficial to have a vast amount of information readily
available in such a small image, it is not an easy task to analyze the information,
impose a structure on it, and reason about it in an efficient manner,
although these tasks might be simple and intuitive for human beings.
The field of computer vision is closely related to many sibling fields
such as signal processing, machine learning, or even cognitive science
in psychology. For example, it leverages techniques in signal processing
to remove the noise in the image data. It also uses machinelearning
methodologies so that machines can “learn” to recognize
objects, such as fruits. Understanding how human beings perceive the
world can inspire new representations of image data and alternative
solutions to some of the computer vision problems.
WHAT IS COMPUTER VISION?
Introduction to the Field of Computer Vision
Originated from the large field of artificial intelligence, computer vision is
concerned with the study of enabling machines to perform visual tasks.
The inputs to machines are images or video sequences, captured through a
live camera feed. These tasks range from low-level de-nosing and filtering,
to mid-level region growing or image/video segmentation (i.e., the operation
of grouping image pixels into semantically uniform entities), and
eventually to high-level detection or recognition (e.g., recognizing objects
or faces in images). The old Chinese proverb, “A picture is worth a thousand
words,” best summarizes the challenges and opportunities of this
field. While it is beneficial to have a vast amount of information readily
available in such a small image, it is not an easy task to analyze the information,
impose a structure on it, and reason about it in an efficient manner,
although these tasks might be simple and intuitive for human beings.
The field of computer vision is closely related to many sibling fields
such as signal processing, machine learning, or even cognitive science
in psychology. For example, it leverages techniques in signal processing
to remove the noise in the image data. It also uses machinelearning
methodologies so that machines can “learn” to recognize
objects, such as fruits. Understanding how human beings perceive the
world can inspire new representations of image data and alternative
solutions to some of the computer vision problems.
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