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