CIS 350
Principles and ApplicationsOf
Computer Vision
Dr. Rolf Lakaemper
May I introduce myself…
• Rolf Lakaemper
• PhD (Doctorate Degree) 2000Hamburg University, Germany
• Since 1/2003 Assist. Professor at Department of Computer and Information Sciences, Temple University
• Main Research Area: Computer Vision
Computer Vision ?
Computer Vision ?
“Computer vision’s great trick is extracting descriptions of the world
from pictures or sequences of pictures”(Forsyth/Ponce: Computer Vision)
Pictures/Movies:
How to
• Represent• Process / Prepare• Handle• Recognize Objects
Representation
• Digital Images• Color Spaces• Gray Images• Binary Images• Geometrical Properties
Representation
• Digital Images• Color Spaces• Gray Images• Binary Images• Geometrical Properties
How to process / prepare:
• Filters• Edges• Geometric Primitives• Lines, Circles
Low Level Object Handling:
• Image / Video Compression• Huffman • JPEG• MPEG• …
Low Level Object Handling:
• Object representation
Low Level Object Handling:
• Segmentation
Object Recognition:
• Color, Texture, Shape
Object Recognition:
• Applications
• Character recognition• Face Recognition• Shape Recognition (Image
Databases)
Central Distance Fourier
(MATLAB DEMO)
3D Distance Histogram
(MATLAB DEMO)
ISS – An Image-Database
using the
ASR – Algorithm
Dr. Rolf Lakaemper
The Interface (JAVA – Applet)
The Sketchpad: Query by Shape
The First Guess: Different Shape - Classes
Selected shape defines query by shape – class
Result
Specification of different shape in shape – class
Result
Let's go for another shape...
...first guess...
...and final result
Query by Shape, Texture and Keyword
Result
CIS 350 Schedule:We: Introduction to topic
Fr: LAB
Mo: Discussion
CIS 350 Schedule:We: Introduction to topic
Fr: LAB
Mo: Discussion