1. Introduction
to
Computer Vision
ashishkhare@jkinstitute.org
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24. goals of field of vision
• understand how animals represent and
process information carried by light, by
– measuring and modeling visual performance
in humans and other animals
– finding ways to build artificial visual systems
– characterizing neural mechanisms that
• implement visual systems
– apply this understanding to obtain medical,
technological advances
25. processing of images in humans
• as a first approximation, rods and cones
(sensory cells in the retina) represent image as
large 2D array of light intensities
– about 126 million sensory cells!
• this image representation is processed by brain
enabling complex cognitive functions
– recognize a familiar face or scene
– disambiguate overlapping objects
– read sloppy handwriting
• how does the brain do all of this? how might
image processing be partitioned into subtasks?
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27. image processing tasks of brain
• possible tasks:
– extraction of contour (e.g. sharp light intensity
changes in the image)
– extraction of motion
– identification of object parts
• still unclear: how are these integrated to
enable us to extract meaning from what
we see?
30. Inattentional Blindness
Mack & Rock (1998)
• Definition: the failure to see consciously, caused by
lack of attention
• We can miss perceiving very obvious changes if we
are not attending. Subjects do not consciously
perceive features of the visual scene that they do
not attend to.
• Subjects were engaged in tasks that demanded a
high degree of attention, such as looking at a cross
and trying to determine which arm is longer.
36. Inattentional Blindness
• 25% of subjects failed to see the square when it was
presented in the parafovea (2° from fixation).
• But 65% failed to see it when it was at fixation!
• What is missed?
– Sad or Neutral face
– A word (priming for the word is present)
• What is not missed?
– Name
– Smiling face
37. Change Blindness
• Change Blindness is the phenomena were
we fail to perceive large changes, in our
surroundings as well as in experimental
conditions.
• Change could be in existence, properties,
semantic identity and spatial layout.
• Attention is required to perceive change,
and in the absence of localized motion
signals, attention is directed by high level
of interest (Rensink et al, 1997).
38. Flicker paradigm
• Basically, alternate an
original image A with a
modified image A’, with brief
blank fields placed between
successive images
39. Change Blindness
• “Visual perception of
change in an object
occurs only when that
object is given focused
attention”
• “In the absence of
such attention, the
contents of visual
memory are simply
overwritten by
subsequent stimuli,
and so cannot be used
to make comparisons”
41. Why CB?
• Change blindness could be due to –
– Poor representation of pre- and post change
scene or
– Pre change representation gets over-written
by post change representation or
– Capacity to retrieve and compare information
is limited (Hollingworth, 2003).
• Color change detection with multi-element
displays
42. Figure-Ground Segregation
• Discovered by Edgar
Rubin (Fig.1, 1921).
• Only one side of the
contour is seen as figure.
• Has shape, appears
closer.
• Background appears
Fig.1 (Faces/vase display)
behind the figure and has
no shape.
43. Background
• Configural cues:
– symmetry
– convexity
– area ………….. Gestalt psychologists
• Lower region
• lower region of a display will be seen as figure than the upper
region. (Vecera et al. 2002)
• Top-bottom polarity
• Stimuli having wide base and narrow top were perceived as
figures than the ones which had narrow base and wide top.
• (Hulleman and Humphreys, 2004)
• Higher cognitive processes
» Object memory (Mary Peterson et al. 1991)
» Attention ( Vecera et al. 2004)
44. Motivation
• Palmer and his colleagues conducted a study in which
they used temporal frequency (flicker) and manipulated
edge synchrony with the two regions (left and right).
• They concluded from their studies that edge plays the
key role in determining figure-ground segregation. In
their study they found that the region with which the
edge synchronizes will be seen as figure irrespective of
whether the region is flickering or not.
• Wong and Weisstein (1987) demonstrated that spatial
and temporal frequencies play a major role in assigning
figural status to a region.
45. Reference Books
• Fundamentals of Digital Image Processing:
Anil K. Jain
• Digital Image Processing: Gonzalez & Woods
• The Image Processing Handbook: J.C. Russ
• Digital Image Processing: B. Jahne
• Image Processing, Analysis and Machine
Vision: M. Sonka, V. Hlavac, R. Boyle
• Computer Vision Handbook: B. Jahne
• Computer Vision: M. Brady
