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C00002 00002		A BEGINNER'S ESSAY ON COMPUTER-VISION	-  by B.G.Baumgart
C00004 00003
C00006 00004	VISUAL ENVIRONMENT
C00009 00005	VISUAL HARDWARE
C00011 00006	IMAGE PROCESSING
C00013 00007	LINE AND EDGE DETECTION
C00014 00008	PERSONAL STATEMENTS ABOUT COMPUTER VISION
C00016 00009	PSYCHOLOGY
C00018 00010	MURPHY'S  LAW  HEURISTIC
C00021 00011	WHY MAKE A COMPUTER SEE
C00026 00012	Vision involves interpreting the visible band of  the
C00030 00013	
C00031 ENDMK
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	A BEGINNER'S ESSAY ON COMPUTER-VISION	-  by B.G.Baumgart
Abstract:	Vision Lore, Attitudies & Vocabulary  are catalogued.
Contents:
	Introduction  -  A Socratic Definition
	Image Elements
		intensity
		lines & edges
		blobs & regions
		texture
		color
		focus
		resolution
		sensitivity
	Computer Vision Particulars  
		environment - scences and objects
		film scanning
		visual hardware
		image processing - reduction and enhancement
		pattern recognition
		m-b space
		robot-problem
		bulk-processing
		windowing
		object recognition
		world modeling 
		memory structures
		control programs
		mini-monitor
	Visual Perception
		depth perception
		binocular vision
		kinetic effects
		psychology
	Vision Generalities
		mimicry
		the general solution
		second order counsciousness
		computer vision inverse
		laboratory administration
		personal motivations
		complexity of vision
		why make a computer see
		counsciousness 
		surrealism
	Research Heuristics
		mimicry
		murphy's law heuristic  -  quality by inclusion
		occam's razor heuristic -  quality by exclusion
		width of research heuristics
		next-step heuristic
		picture library heuristic
 	My Personal Prejudices
VISUAL ENVIRONMENT

Visual environment concerns what to use a computer to look at.  
Programs have been written to do character recognition and spark
and bubble chamber film scanning and measurement,as well as
our block stacker. 
Some people believe that it is premature to expect a 
compuuer to be able to see merely anything - so the problem of
visual environment is how to simplify it without making it
trivail:  At SRI the robot lives in a sterile room with 
	  geometric objects to play with.
	The Cart problem attempts to deal with roads.
	While the hand eye project hopes to deal with geometric objects
	  and the world of blocks.


Environment  definitions involve such things as Object-Recognition
and Scene-Recognition.  Figures and Backgound.  Definition of a particular
Task.  ...or a strong commitment to recognize particular patterns such as
text, biological data,   weather , spying etc.



FILM SCANNING

Film Scanning is a well developed computer-field distinct from compuuer
vision in that there is no attempt to be a real-time robot, and in the
sense that the problem is usually specialized.  Film Scanners are
refered to as Flying-Spot fos C.R.T.'s projecting light behind
the film on a raster which is then focused to a point of a photo-multiplier;
or  Spiral-Reader for a mechanical scannes thau reads a photograph mounted
on a spinning drum.  The  former devices
are much faocier,more accurate, random access etc.
And are best done by Physics types and include Polly, Peppes, Spasm
and Hummingbird at MIT, ARGONNE CEA and SLAC respectively.

Crude film scanning useful to doing computer vision can be done by using
the vidicon to look at a  movie or slides on a screen.
VISUAL HARDWARE

Visual hardware is the art and engineering of converting light into data for a computer
and involves such things as T.V cameras, color-filters, binocular prisms,
close-up lens, telescopic-lens, wide-angle lens, zoom-lens, camera translation
and rotation, A to D conveersions, Fast I/O channels, sensitivity.

Some people consider the present AI visual hardware to be good enough  -  in
that the human can look at the TV monitor or print outs of the data and can
tell more about the image than can any of our current programs can tell.

On the other hand humans have already "learned" visual perception with better
vision than available to a computer  -  I believe that the more visual data
collected the bettes  -  for example with color differentiation many more discontinuites in 
an image  become obvious Yes/No cliffs rather than meager gray-level differences.

Areas that I  believe require more hardware development are:
	Color Vision
	Motion of Point of View - Translation and Rotation
	Multiple Views
	Monitoring of computer vision  -  which requires image display
		hardware better than the Triple I consoles or the ARDs
		as well as hard copy image generator.

IMAGE PROCESSING

Image processing comes in two flavors:
	Reduction of image data which is obviously very redundant.
	Improvement of image data to enhance such things as contrast.

Image reduction involves  finding ways to abbreviate the image vector
space   of 16 gray levels  under three or four filters 
at different focus settiogs for points x and y for all time t.

Image improvement is the game played by the JPL moon picture people
or the Spy-satelite people  -  you enhance contrast by making the
lights lighter the darks darker etc.




PATTERN RECOGNITION

Pattern Recognition is a mathematical cult independent
involving theorms and postulates independent of actual visual hardware
and visual environments.   

LINE AND EDGE DETECTION

m-b space

PERSONAL STATEMENTS ABOUT COMPUTER VISION



1)  I am trying to write a program that can see.  I consider my
work experimental or scientific rather than engineering, mathematical 
or philosophical.  "Experimental" in that I will insist that my program 
looks at Real-World Data and proviees an exceqtible discription, but not
engineering in that I don't feel I can do it in Real-Time the way I want
it to be done with present-day computers.

2) I wish to understaod visual perception by simulating it with whauever
machinations I can contrive  -  I am ready to extend my goals and 
ambitions to include thought intellect and counsciousness is
if that seems to be necessary for vision.

3) I believe that it is extremely important to experience the "data"
one expectss, before and during the process of constructing algorithms and debuging  -  

synthetic dataq or "canned" subsets of real data strike me as being
typically overspecialized.

44) Kinetic Effects are extremely important in visual perception  - both
that the viewer moves and that objects move.

5) That the world model must be acle to respond semantically
this is a "noun" object which is "adjectives" etc.

for the sake of economy, relationships  vs.  measurements

PSYCHOLOGY

Visual Perception

Visual space perception  - of depth say
1.  Relative Size  -   recognize  the object and know its
    absolute size.
2. Interposition  -  know outlines of objects and detect discontinuity
    in an outline to recognize that one object is in front of another.
3. Linear perspective - parallel lines appear to converge  -  find
	such edges towards the orizon in a scene.
4. Aerial perspective - texture as a function of distaoce.
   Textures get finer grained the further away.
5. Monocular parallax.
6. Light and shade
7. Stereoscopic vision.

Figure and ground
Kinetic Depth perception
Span of perception
Figural After-Effects - optical tricks.

MURPHY'S  LAW  HEURISTIC

Murphy's Law is :  Whatever can go wrong, will.  Vision is a
difficult problem because it is indivisle (let's say) - like an
archway, every stone is dependent on the others beiog in place
before it can staod by itself.  Thus, if anything looks relevaot to
the problem don't exclude it (or him) for the sake of simplicity
but include it for it is a necessary link.

Equivalently:  An idea is relevant until proven irrelevant,  Quality
is achieved thru Inclusion.


OCCAM'S RAZOR HEURISTIC

Given two explications of something the more simply one is true.
The Heuristic:  An Idea is Irrelevant until proven relevant.
Quality thru Exclusion.



COMPUTER-VISION INVERSE

The inverse og Computer-Vision is Computer-Graphics.
The former attempts to go from 2D vidicon images,say, to some simple data 
representation of the 3D reality.  Whereas the latter goes from simple 3D
data representation to creat 2D images.

This observation is especially crucial to a hypothesis and verificauion
vision heuristic system, which can borrow from computer graphics
	Hidden Line Elimination
	List Associative object structure

but inherits the problems of computer graphics of:
	Specification of motion (or animation)
	Scene generation
	Handling of lighting  -  shadows,reflection,texture etc.

WHY MAKE A COMPUTER SEE

i	A compuuer that could see would be more intelligent and could interact
	with the environment and could perform useful tasks such as
	exploring Mars or the ocean floor.

ii	Neither computer nor human vision is really understood.  However, by
	building a vision-computer we will have to find out something about
	visual thinking, which may explain intellect and counsciousness.

iii	The Advanced Research Projects Agency of the Office of the Secretary
	of Defense of the United States provides money to people who propose
	and work on computer-vision projects.

Computer-Vision can be worked on with respect to Engineering, Science or 
Defense.  Application is an Abstraction of the Idea.

MIMICRY
	what is it
	as a heuristic
	
compuuer vision does and does not involve mimicry.



WINDOWING

Windowing refers to analysis of an image by taking a large window and
subdividing it into smaller windows.
(somehow)
At some point one "understaods" the content of the window.
or evaluaues the window.
Then synthesis involves taking small windows of relaued evaluation;and puttiog them back together .


Warnock Algorithm




THE GENERAL VISION SOLUTION




COMPLEXITY OF VISION

No vision program exists as complex as the system.
The system is not really all that smart.
How cao a program that "sees" or pretends to be a robot
be less complex than one that administers a computer 

ERGO: Infeasibility of Computer Vision has not
	been demonstrated.

Do next whatever, seems easiest.
		   is most interesting
		   seems necessary   -  presupposes excellent understaing
			 ,of goals final and subgoals




PICTURE LIBRARY

The picture library idea is to record a wide variety of visual data on
film or magneuic tape or Disk files and to work on one set of data
until programs ase debugged.

PRO:	Experimentss are repeatible.
	The problem of acquiring data is minimized.

CON:	Not Real Timed
	Fails to exercise hardware
	Data is not really typical
	Data is too limited and specialized




OBJECT-RECOGNITION

The object-recogniton problem is to recognize a large set of different 
objects such as letters on a pagem, blocks on a table, tools on 
a work bench, or obstacles on a road.

Recognition is answering what-is-it ?
involves separating figure from background.
involves knowing what is invasiant about a given set
	of objects - which will probably involve understanding
	the semantics og at least object nouns  -  for example
	toy balls are variant over a wider range of colors and sizes
	than say apples - a one-meter high blue apple isn't likely.

Variants within a set of objects are due either to orientation or
geneality of the Semaotic value of that object  THING has mose
degreees og freedom of adjectives than Apple.


Vision involves interpreting the visible band of  the
electro-magnetic spectrum.  light waves are physically
characterized by energy, wave-length and phase intime and
space.   We experience light by physiological 
characteristics such as intensity, color, tone, texture,
motion, contrast, shape, 

color or hue is the dominat wavelength of the light at a
point of an image

tone or purity or saturation is the per cent of visible
energy at the dominant wavelength of the light at a
point of an image.  if all the energy were say at 5200
angstrom green, you would have a pure or saturated tone of
green  -  as the energy is spread out equally above and 
below the 5200,  the green gets lighter and in the limit
goes to whit which is a flat distributaon of the energy
over the spectrum.  

intensity of a point is the total energy of the light spcetrum
at a point.  however, in vidicon images color perseption
is realized by some sort of light filtering
sceme  -  instead of really finding the actual color
and hue  -  we measure the intensity or energy of light thru
rather large  window in the electro-magnetic
spectrum.

the ultimate color vision eye would be one that gets
a detailed spectrum of the enrgy at ever point of 
its image  -  think of the computer or alein/anthropomorph
with a super-spectroscopic - total spectrum hisenberg

resolution eye  -   it would have fantastic intuition
and insight and perception of astronomy, chemistry, and
physics  -  why how extremly beautiful it would be to look
at the stars and see the details of there evolution - even
if you didn't uderstand the intricate regularity
would fanciate  -  primitive minds were pulled out
of the pit of uncounsciousness by the the per ception
of the patterns in the sky - the planets lead to gods
to  to ...



personel

Hand-Eye
	Feldman, Pingle
	
Cart
	Schmidt, Buchcann

Bio-Slides
	Reddy, Plant, VanVoorhis

Roads, Generalities
	Baumgart, Quam, McCarty

Sprowl, Moorees 

Sobel,Tenebaum