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.
