1. CSE 455 Computer Vision Autumn 2010
Professor Linda Shapiro
TA: Alfred Gui

2. Introduction What IS computer vision?
Where do images come from?
The analysis of digital images by a computer
You tell me!

3. Applications: Medical Imaging
CT image of a
patient’s abdomen
liver
kidney
kidney

4. Visible Man Slice Through Lung

5. of the Blood Vessel Tree
3D Reconstruction
of the Blood Vessel Tree

6. Mouse Eye Image Retrieval
for Genetic Studies

7. Robotics 2D Gray-tone or Color Images 3D Range Images What am I?
“Mars” rover
What am I?

8. Robot Soccer

9. Image Databases: Images from my Ground-Truth collection:
Retrieve images containing trees

10. Some Features for Image Retrieval
Original Images
Color Regions
Texture Regions
Line Clusters

11. Documents:

13. Science Previous Classification Results: Calineuria (Cal)
Doroneuria (Dor)
Yor (Yor)
Previous Classification Results:
Classified
as Cal
as Yor
Cal
171 16
Yor 99
Classified
as Cal
as Dor
Cal
114 72
Dor 70
133
UW and Oregon State University

14. Soil Mesofauna TraychetesA XenillusA ZyqoribafulaA AchipteriaA
BdellozoniumI
BelbaA
BelbaI
CatoposurusA
EniochthoniusA
PtenothrixV
PtiliidA
HypochthoniusLA
EntomobrgaTM
EpidamaeusA
EpilohmanniaA
EpilohmanniaD
EpilohmanniaT
QuadroppiaA
HypogastruraA
LiacarusRA
MetrioppiaA
IsotomaVI
NothrusF
IsotomaA
onychiurusA
TomocerusA
PlatynothrusF
OppiellaA
SiroVI
PeltenuialaA
PhthiracarusA
PlatynothrusI

15. Surveillance: Event Recognition
in Aerial Videos
Original Video Frame
Color Regions
Structure Regions

16. 2D Face Detection

17. Face Recognition
Glasgow University

18. 2D Object Recognition from “Parts”
Oxford University

19. Graphics: Special Effects
Andy Serkis, Gollum, Lord of the Rings

20. 3D Reconstruction and Graphics Viewer

21. 3D Craniofacial Shape Analysis
from Meshes of Children’s Heads

22. Digital Image Terminology:
pixel (with value 94)
its 3x3 neighborhood
region of medium
intensity
resolution (7x7)
binary image
gray-scale (or gray-tone) image
color image
multi-spectral image
range image
labeled image

23. The Three Stages of Computer Vision
low-level
mid-level
high-level
image image
image features
features analysis

24. Low-Level
sharpening
blurring

25. Low-Level Mid-Level Canny original image edge image ORT data structure
circular arcs and line segments

26. Mid-level K-means clustering (followed by connected component
analysis)
regions of homogeneous color
original color image
data
structure

27. Low- to High-Level edge image consistent line clusters
low-level
edge image
mid-level
consistent
line clusters
high-level
Building Recognition