browsing large image datasets through voronoi diagrams

24
Browsing large image datasets through Voronoi diagrams Paolo Brivio, Marco Tarini, Paolo Cignoni

Upload: sabine

Post on 24-Feb-2016

46 views

Category:

Documents


0 download

DESCRIPTION

Browsing large image datasets through Voronoi diagrams. Paolo Brivio , Marco Tarini , Paolo Cignoni. Targeted image datasets. Fairly large datasets (i.e. 1000s images) cannot be all visible at the same time Non-uniform image aspect ratio landscape vs portrait image orientation - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Browsing large image datasets through  Voronoi  diagrams

Browsing large image datasetsthrough Voronoi diagramsPaolo Brivio, Marco Tarini, Paolo Cignoni

Page 2: Browsing large image datasets through  Voronoi  diagrams

• Fairly large datasets (i.e. 1000s images)• cannot be all visible at the same time

• Non-uniform image aspect ratio• landscape vs portrait• image orientation

• Total ordering• e.g. time of shot, some ordering defined over calibration,

user-defined sequence, etc.• Allow to specify per-image importance• i.e. each image represents a subset of the dataset

Targeted image datasets

Page 3: Browsing large image datasets through  Voronoi  diagrams

• Rectangular grid of image thumbnails• [opt] on scrolling panels

Conventional image browsers (fullscreen)

Explorer

by Microsoft

Google

Image

by Google

FastStone

Picasa3

by Google

Page 4: Browsing large image datasets through  Voronoi  diagrams

• Sequence of image thumbnails• [opt] scrollbars or buttons

PhotoC

loudby IS

TI-CN

RFastS

toneConventional image browsers (thumbnail bars)

Picasa3 by G

oogle

Page 5: Browsing large image datasets through  Voronoi  diagrams
Page 6: Browsing large image datasets through  Voronoi  diagrams

Other drawbacks: non-uniform aspect ratios

wasted space

Google Im

age

Page 7: Browsing large image datasets through  Voronoi  diagrams

A new type of thumbnail bar

focusimage

Page 8: Browsing large image datasets through  Voronoi  diagrams

Thumbnail sizes

focusimage

far from focus:small thumbnails

near to focus:large thumbnails

Page 9: Browsing large image datasets through  Voronoi  diagrams

Thumbnail sizes

focusimage

thum

bnai

l siz

e

distance from focusin image list0

(focus image)±10 ±20

Page 10: Browsing large image datasets through  Voronoi  diagrams

Clustering images

focusimage

far from focus:each thumbnail

represents many images

near to focus:1 thumbnailfor 1 image

Page 11: Browsing large image datasets through  Voronoi  diagrams

Selecting visible images

focusimage

41 2 3 5 6 7

visibleimage

hiddenimage

repr

esen

tativ

enes

s

imagenumber

custo

m

fuctio

n

focus

Page 12: Browsing large image datasets through  Voronoi  diagrams

Spatial ordering

focusimage

previous imagesin the ordering

following imagesin the ordering

x-axis: image ordering respected

y-ax

is:

arbi

trar

y

Page 13: Browsing large image datasets through  Voronoi  diagrams

• Define a parametric domain in which the ordering is enforced• Arbitrary thumbnail-bar shape

custom parametric

function

Not only horizontal thumbnail bars

Parametric domain

Thumbnail-bar shape

enforce ordering

Page 14: Browsing large image datasets through  Voronoi  diagrams

Transitions

focusimage

new focus

focusimage

Packing of thumbnails• arbitrary bar shape• irregular shaped

thumbnails• varying size• fitting

aspect/orientation• image ordering respected• 1 thumbnail per image

cluster

Page 15: Browsing large image datasets through  Voronoi  diagrams

Transitions

newfocus

Packing of thumbnails• arbitrary bar shape• irregular shaped

thumbnails• varying size• fitting

aspect/orientation• image ordering respected• 1 thumbnail per image

cluster

Animated transition

withtemporal

coherence

Page 16: Browsing large image datasets through  Voronoi  diagrams

Autorecentering Voronoi diagrams

• Voronoi diagram:• given a set of 2D “seeds” inside a 2D figure F• partition F into as many “regions”• a point belongs to the region of the closest seed

• Autorecentering step (Lloyd relaxation):• move seed (●) of each region in its barycenter (+)

x nx 1

Page 17: Browsing large image datasets through  Voronoi  diagrams

Taming autorecentering Voronoi diagrams

Page 18: Browsing large image datasets through  Voronoi  diagrams

Taming autorecentering Voronoi diagrams 1/2

• Weighting for region size differentiation• Power Diagram

• Dynamic weight balancing • match required region sizes• smooth transitions

• including: smooth appear/disappear of regions• Ordering enforcing (over “x”)• interleaved with recentering step

• Anisotropy: make regions appropriate• …aspect ratio• …orientation (non axis-aligned)

Page 19: Browsing large image datasets through  Voronoi  diagrams

Taming autorecentering Voronoi diagrams 2/2

• Stabilization• prevent oscillations

• Small extra forces• pulling regions toward expected positions• accelerate convergence

• Accept user “dragging” mouse gesture• Real time computation• efficient GPU implementation

Page 20: Browsing large image datasets through  Voronoi  diagrams

Tamed autorecentering Voronoi diagrams

Packing of thumbnails• arbitrary bar shape• irregular shaped

thumbnails• varying size• fitting

aspect/orientation• image ordering respected• 1 thumbnail per image

cluster

optional bulge-out effect

Animated transition

withtemporal

coherence

Page 21: Browsing large image datasets through  Voronoi  diagrams

Thumbnail creationor

igin

al

imag

ere

gion

sh

ape

+ resizing- cropping

- resizing+

cropping

+

Page 22: Browsing large image datasets through  Voronoi  diagrams

Thumbnail creation: with per-image orientationor

igin

al

imag

ere

gion

sh

ape

+ resizing- cropping

- resizing+

cropping

+

Page 23: Browsing large image datasets through  Voronoi  diagrams

Example

Page 24: Browsing large image datasets through  Voronoi  diagrams

More examples