Vision Recognition Neil Agarwal Bailey Zhang Zack Sorenson

1
Vision Recognition

• Neil Agarwal
• Bailey Zhang
• Zack Sorenson
• Ben Schneider

2
What is Computer Vision?

• Definition
• Computational Vision
• Attempts to understand visual perception and
  understanding
• Machine Vision
• Attempts to create practical application for
  computer vision

3
Vision Recognition AI

• Creating useful autonomous agents
• Human/computer interfacing
• Gesture recognition
• Handwriting recognition
• Passive observation analysis
• Understanding biological vision

4
Hondas ASIMO
5
GRACE the Robot
6
Converting handwritten figures into figures
usable by a computer
7
(No Transcript)
8
Current ImplementationOptical Character
Recognition (OCR)

• Types of OCR
• Character-based word recognition
• Segmentation-based word recognition
• Word-shape recognition
• Current Limitations of OCR
• Underlines in text
• I and i confusions
• Distortion of e
• Examples of OCR software
• Calera Wordscan Plus 1.0
• Caere Omnipage Professional 3.0
• Xerox Imaging Systems AccuText 3.0

9
Current Implementation (cont.)

• Scarecrow
• Floating, autonomous robot platform powered by
  solar panels
• Searches for birds using its vision system
• Goes around, when its senses birds, bumps them or
  shoots water at them
• Floats in catfish ponds to protect the stock
  which is frequently depleted by hungry birds

10
Successes in Computer/MachineVision

• Machine Vision, the name for Computer Vision that
  is applied specifically to robots or machines, is
  extremely relevant in industry.
• Most Computer Vision technology that affects you
  is in fact Machine Vision.

11
Machine Vision and You

• Machine Vision is being developed to control the
  quality of products, detecting defects
  automatically
• The technology is reaching a point where people
  can be tracked in 3D, leading to more robust
  security systems.
• And for your entertainment, Machine vision is
  being developed to track actual movements, for
  more realistic and exciting games

12
Other Machine Vision Fields

• Agriculture, Architecture, Character Recognition,
  Cultural, Forensic, Medical, Image Processing,
  Reverse Engineering, Military, Navigation, Remote
  Sensing, Safety, Sports

13
Successes in Computer Vision

• Computer Vision is broader than Machine Vision.
• There are many successes in Computer Vision
  many, many, many successes

14
Development/Successes in Computer Vision
Technology

• SUCCESSOR

15
General Successes

• Marrs Theory shape info from images.

16
Marrs Theory

• The geometry
• The reflectance of the visible surfaces
• The illumination
• The viewpoint

17
More Marr
18
Problems Setbacks

• Finding 3D objects in 2D images
• Making raster images usable for a computer
• Incomplete understanding of human vision

19
Whats Currently Being Done

• Penn State Computer Vision Lab
• Berkeley Group

20
Penn State

• Hand gesture recognition as supplement to speech
  recognition.
• Text recognition and clarification in video.

21
Text Clarification

• Possible example need for technology

22
Berkeley

• Automatic detection of human nudes
• Image content recognition

23
Image Content Analysis
24
Future of Vision Recognition

• PCs Recognizing Users (Microsoft Project)
• When a user sits in front of the computer, it
  will bring up his work, etc.
• PC equipped with a camera on top
• Long term aiming for a system that can recognize
  eye movements, so that software could be
  controlled by eye movement
• Only a couple years from reaching mass market?

25
Future of Vision Recognition (cont.)

• Augmented Reality

Real world
Augmented world
26
Any Questions?