Upload
others
View
1
Download
0
Embed Size (px)
Citation preview
Lecture 12 - 3-Nov-2016Fei-Fei Li
Lecture 12 - 3-Nov-2016Fei-Fei Li
•••
Lecture 12 - 3-Nov-2016Fei-Fei Li
Salvador Dalí “Man/couple with sleeping dog" (1948)
Lecture 12 - 3-Nov-2016Fei-Fei Li
•
Slide credit: Steve Seitz, Kristen Grauman
Lecture 12 - 3-Nov-2016Fei-Fei Li
•
Slide credit: Svetlana Lazebnik
Lecture 12 - 3-Nov-2016Fei-Fei Li
•
Berkeley Segmentation Dataset [Martin et al., ICCV 2001]
Lecture 12 - 3-Nov-2016Fei-Fei Li
••
“superpixels”
Slid
e cr
edit
: Sv
etla
na L
azeb
nik
Lecture 12 - 3-Nov-2016Fei-Fei Li
50x50 Patch50x50 Patch
Lecture 12 - 3-Nov-2016Fei-Fei Li
[Felzenszwalb and Huttenlocher 2004]
[Mori et al. 2005]
Lecture 12 - 3-Nov-2016Fei-Fei Li
“GrabCut” [Rother et al. 2004]
Lecture 12 - 3-Nov-2016Fei-Fei Li
Oversegmentation Undersegmentation
Multiple Segmentations
Lecture 12 - 3-Nov-2016Fei-Fei Li
Lecture 12 - 3-Nov-2016Fei-Fei Li
•––
•–
•–
•–
Lecture 12 - 3-Nov-2016Fei-Fei Li
•–
•–
•–
•–
Lecture 12 - 3-Nov-2016Fei-Fei Li
•–
•–
•–
…→
Lecture 12 - 3-Nov-2016Fei-Fei Li
Slide credit: Kristen Grauman
What things should be grouped?
What cues indicate groups?
Lecture 12 - 3-Nov-2016Fei-Fei Li
•••
Lecture 12 - 3-Nov-2016Fei-Fei Li
Slide credit: Kristen Grauman
Lecture 12 - 3-Nov-2016Fei-Fei Li
Slide credit: Kristen Grauman
[ ][ ][ ]
Lecture 12 - 3-Nov-2016Fei-Fei Li
Slide credit: Kristen Grauman
Lecture 12 - 3-Nov-2016Fei-Fei Li
Slide credit: Kristen Grauman
Lecture 12 - 3-Nov-2016Fei-Fei Li
Lecture 12 - 3-Nov-2016Fei-Fei Li
•
Lecture 12 - 3-Nov-2016Fei-Fei Li
●
[Gregory 1968]
Lecture 12 - 3-Nov-2016Fei-Fei Li
●
[Gregory 1968]
Lecture 12 - 3-Nov-2016Fei-Fei Li
••
Slid
e cr
edit
: Sv
etla
na L
azeb
nik
Lecture 12 - 3-Nov-2016Fei-Fei Li
•––
•
Untersuchungen zur Lehre von der Gestalt,Psychologische Forschung, Vol. 4, pp. 301-350, 1923
“I stand at the window and see a house, trees, sky. Theoretically I might say there were 327 brightnesses and nuances of colour. Do I have "327"? No. I have sky, house, and trees.”
Max Wertheimer(1880-1943)
Lecture 12 - 3-Nov-2016Fei-Fei Li
●
Imag
e so
urce
: Fo
rsyt
h &
Pon
ce
Lecture 12 - 3-Nov-2016Fei-Fei Li
Imag
e so
urce
: Fo
rsyt
h &
Pon
ce
Lecture 12 - 3-Nov-2016Fei-Fei Li
Imag
e so
urce
: Fo
rsyt
h &
Pon
ce
Lecture 12 - 3-Nov-2016Fei-Fei Li
Imag
e so
urce
: Fo
rsyt
h &
Pon
ce
Lecture 12 - 3-Nov-2016Fei-Fei Li
Imag
e so
urce
: Fo
rsyt
h &
Pon
ce
Lecture 12 - 3-Nov-2016Fei-Fei Li
https://en.wikipedia.org/wiki/Rubin_vase
Lecture 12 - 3-Nov-2016Fei-Fei Li
https://en.wikipedia.org/wiki/Rubin_vase
Multistability
Lecture 12 - 3-Nov-2016Fei-Fei Li
Man and crane, Mimbres culturepot, c. 1000 -1150 AD
second century B.C. Greek mosaic from the Acropolis
Lecture 12 - 3-Nov-2016Fei-Fei Li
Lecture 12 - 3-Nov-2016Fei-Fei Li
•••
Lecture 12 - 3-Nov-2016Fei-Fei Li
Lecture 12 - 3-Nov-2016Fei-Fei Li
(or bottom-up hierarchical clustering)
Simple algorithm
● Initialization: ○ Every point is its own cluster
● Repeat:○ Find “most similar” pair of clusters○ Merge into a parent cluster
● Until:○ The desired number of clusters has been reached○ There is only one cluster
Lecture 12 - 3-Nov-2016Fei-Fei Li
● Initialization: ○ Every point is its own cluster
Lecture 12 - 3-Nov-2016Fei-Fei Li
● Initialization: ○ Every point is its own cluster
● Repeat:○ Find “most similar” pair of
clusters
Lecture 12 - 3-Nov-2016Fei-Fei Li
● Initialization: ○ Every point is its own cluster
● Repeat:○ Find “most similar” pair of
clusters○ Merge into a parent cluster
Lecture 12 - 3-Nov-2016Fei-Fei Li
● Initialization: ○ Every point is its own cluster
● Repeat:○ Find “most similar” pair of
clusters○ Merge into a parent cluster
Lecture 12 - 3-Nov-2016Fei-Fei Li
● Initialization: ○ Every point is its own cluster
● Repeat:○ Find “most similar” pair of
clusters○ Merge into a parent cluster
Lecture 12 - 3-Nov-2016Fei-Fei Li
----
---
dist
ance
Lecture 12 - 3-Nov-2016Fei-Fei Li
●○
http://scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering.html
Lecture 12 - 3-Nov-2016Fei-Fei Li
●
●
Lecture 12 - 3-Nov-2016Fei-Fei Li
••••
••••
Lecture 12 - 3-Nov-2016Fei-Fei Li
•••