Traditionally, scientific fields have defined boundaries, and
scientists work on research problems within those boundaries.
However, from time to time those boundaries get shifted or blurred
to evolve new fields. For instance, the original goal of computer
vision was to understand a single image of a scene, by identifying
objects, their structure, and spatial arrangements. This has been
referred to as image understanding. Recently, computer vision has
gradually been making the transition away from understanding single
images to analyzing image sequences, or video understanding. Video
understanding deals with understanding of video sequences, e. g.,
recognition of gestures, activities, facial expressions, etc. The
main shift in the classic paradigm has been from the recognition of
static objects in the scene to motion-based recognition of actions
and events. Video understanding has overlapping research problems
with other fields, therefore blurring the fixed boundaries.
Computer graphics, image processing, and video databases have
obvious overlap with computer vision. The main goal of computer
graphics is to gener ate and animate realistic looking images, and
videos. Researchers in computer graphics are increasingly employing
techniques from computer vision to gen erate the synthetic imagery.
A good example of this is image-based rendering and modeling
techniques, in which geometry, appearance, and lighting is de rived
from real images using computer vision techniques. Here the shift
is from synthesis to analysis followed by synthesis."
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