Visual Image Retrieval & Localizationhttp://viral.image.ntua.gr/

Natasa SofouNational Technical University of Athens

EUScreen Workshop, Mykonos, 24 June 2010

A brief introduction

• There is a continuously growing volume of publicly available photos and videos.

• This results to a growing need for automatic metadata generation, concept detection, search, retrieval and analysis of large-scale diverse and heterogeneous visual content.

• Towards this direction the tool presented here is a web based system that aims to retrieve visually similar images and to determine their location by exploiting the available socially created metadata.

The basic idea

• Let’s collect photos• And build a tool • That uses visual similarity• Under any viewpoint• To localize any user photo• To identify landmarks• & link them to wikipedia • In (almost) real time

Let’s collect photos…

• ~1.100.000 photos from

• all geo-tagged during a recent period

• depicting urban landscapes (city centers)

• download all photos & metadata

•

e.g. from London…

W 0°9’25” W 0°5’31”

N51°31’12”

N51°29’35”

~25km2

and build a tool...

that uses visual similarity...

under any viewpoint...

... to localize any user photo

... to identify landmarks

... & link them to Wikipedia

in (almost) real-time!!!• query image analysis: <1.0 second • average response time: <4.0 seconds per query

VIRaLhttp://viral.image.ntua.gr

Natasa

Now: a stroll around Thames…

Phivos

... and their photos!!!

1. Localize Phivos’s photos on the map

2. Align with Natasa’s photostream

3. Group wrt time, location & similarity

londonbig ben

london eyethames

londonbus

tategallery

milleniumbridge

st paulscathedral

thamesriver

towerbridge

4. Add tags & arrange like a photo album

big benlondon eyethames

phivostower bridge

natasanatasa

5. Add tags to regions & names to faces

me

my friendsmy network

PhivosJune 08

YiannisMay 03

KostasMay 05

MariaJan 01

albums i can access

Now, when I go to London…

Thank you !!!