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