This document summarizes a seminar presentation on computer vision and technological advancements. It discusses concepts like infinite computing with the brain, introduction to computer vision including goals and related fields. It covers applications of computer vision like face detection, object detection and tracking, and object recognition. It also discusses advantages and disadvantages of computer vision as well as hazards of technologies like Google Glass. Finally, it presents recent works on motion microscopy and visual microphone by Michael Rubinstein and Fei Fei Li's ImageNet concept to train machines to recognize objects through large image datasets and CNN algorithms.

1. A
SEMINAR
PRESENTATION
ON
“Introduction To Computer Vision And
Technological Advancements”
SUBMITTED TO: SUBMITTED BY:
MR. P.K. JAIN MR. NITIN SHARMA
READER BRANCH - EC
EC-DEPARTMENT SECTION - A
SKIT JAIPUR ROLL NO – 12ESKEC046

2. CONTENTS
1. Concept of Infinite Computing with Brain
2. Introduction to Computer Vision
3. Applications of Computer Vision
4. Advantages of Computer Vision
5. Disadvantages of Computer Vision
6. Hazards of Computer Vision
7. Michael Rubinstein’s Motion Microscope and Visual
Microphone
8. Fei Fei Li’s Concept of IMAGENET

3. 1. Concept of Infinite Computing with Brain

4. ∞

6. 2. INTRODUCTION TO COMPUTER VISION
• Computer Vision is a discipline that studies how to reconstruct, interpret and
understand a 3D scene from its 2D images in terms of the properties of the structure
present in the scene.
• Computer Vision is a field that includes methods for acquiring, processing, analyzing,
and understanding images and, in general, high-dimensional data from the real
world in order to produce numerical or symbolic information, e.g., in the forms of
decisions.
• The ULTIMATE GOAL is for computers to emulate the striking perceptual capability of
human eyes and brains-or even to surpass and assist the human in certain ways

7. RELATION BETWEEN COMPUTER VISION AND VARIOUS OTHER FIELDS

8. 3. APPLICATIONS OF COMPUTER VISION
(a) FACE DETECTION
• Face detection can be
regarded as a specific case
of object-class detection. In
object-class detection, the
task is to find the locations
and sizes of all objects in an
image that belong to a
given class.
• Face-detection algorithms
focus on the detection of
frontal human faces. It is
analogous to image
detection in which the
image of a person is
matched bit by bit.

9. (b) OBJECT DETECTION AND TRACKING
• The DARPA Grand
Challenge is a prize
competition for American
autonomous vehicle,
funded by the Defence
Advanced Research
Project Agency, the most
prominent research
organization of the
United States
Department of Defence.

10. (c) OBJECT RECOGNITION
• The ability of humans to recognize
thousands of object categories in
cluttered scenes, despite variability in
pose, changes in illumination and
occlusions, is one of the most surprising
capabilities of visual perception, still
unmatched by computer vision
algorithms.
• Object recognition is generally posed as
the problem of matching a representation
of the target object with the available
image features, while rejecting the
background features

11. 4. ADVANTAGES OF COMPUTER VISION
• No limitation like as human perception.
• Do not need to have devices embedded, physically printed, or externally
attached to objects targeted for detection.
• Upgrading image sensors does not require upgrading tags, identifiers, or
transponder devices.
• Image capturing devices are easy to mount, remove, replace, and upgrade.

12. 5. DISADVANTAGES OF COMPUTER VISION
• Data processing and analytics is intensive and requires large amounts of
computation resources and memory.
• Fundamental technical limitation is its robustness in the face of changing
environment.
• Illumination variation further complicates the design of robust algorithms
because of changes in shadows being cast.

13. 6. HAZARDS OF COMPUTER VISION
(A)

14. (B)
• Google Glass is already raising concerns
regarding the intrusion of privacy, and the
etiquette and ethics of using the device in
public, where people could be recorded without
permission.
• There are also safety and security concerns as
well for the people wearing Google Glass.
• The places where Google Glass has been
already banned are banks/ATMS, sports arenas,
concert venues, dressing rooms, movie theaters,
cars, hospitals, classrooms, strip clubs, casinos,
bars, etc.

15. (C)

16. 7.1 - MICHEAL RUBINSTEIN’S – MOTION MICRSOSCOPE

18. What they actually did…

19. Overview of EVM (Eulerian Video Magnification)

20. • Take a look at this video to better understand the concepts…

21. 7.2 - MICHEAL RUBINSTEIN’S – VISUAL MICROPHONE

23. Capturing a soundless video and then generating the sounds using the vibration
produced in the chip bag…

24. • A model of a visual microphone as a system that operates on sound

26. 7. FEI FEI LI’S CONCEPT OF IMAGENET
“If We Want Machines to Think, We Need to Teach Them to See”

27. AIM OF IMAGENET
• To train the machine to recognize the input object.

28. • To train the objects a mathematical model is used identifying the face as
a circular object with circular eyes and body structure related to cat.

29. • But if this happens… then model will fail….

30. • This gave rise to a large classified data set called IMAGENET

31. IMAGENET + MACHINE + CNN ALGO = CORRECT RESULT

32. Some more results of IMAGENET so obtained are:

33. • But it still fails a no. of times… so there are chances of improvement yet….

34. THANK YOU…
ALL QUERIES WILL BE APPRECIATED…!!!