Sharing Lifelog Experiences

ODCSSS 2008

Paula MeehanDCUProf. Noel O Connor, Daragh Byrne

Contents Introduction Background Research Event Segmentation Matching Events (1) Matching Events (2) Progress Model

Introduction What is a Lifelog?

Connecting different user’s Lifelog Collections.

Background Research CDVP (Centre for Digital Video Processing)

Event Segmentation

Content and Context in Multimedia Semantics

MPEG feature extraction

Event SegmentationA day’s SenseCam images (3,000 – 4,000)

Multiple Events

Finishing work in the lab

At the bus stop

Chatting at Skylon Hotel lobby

Moving to a room

Tea time On the way back home

Event Segmentation

A day’s SenseCam images (3,000 – 4,000)

Multiple Events

Finishing work in the lab

At the bus stop

Chatting at Skylon Hotel lobby

Moving to a room

Tea time On the way back home

Event Segmentation

Share Events

Event-Segmented image sets

User 1

User 2

Compare Event-Event similarity between Users

Event’s attended by both Users

...

:Similarity matrix

Matching Events (1)

Similarity Score

:

• Scalable Colour• Colour Structure• Colour Layout • Colour Moments• Edge Histogram• Homogeneous Texture

Extract MPEG-7 descriptors for this image

• Scalable Colour• Colour Structure• Colour Layout • Colour Moments• Edge Histogram• Homogeneous Texture

Extract MPEG-7 descriptors for this image

:

User 2 User 1

Matching Events (2)

Progress Presently

Parsing ‘sensor.txt’ and ‘image.xml’ files

Future Work Plot data and compare Extract MPEG-7 Descriptor features of images Match Events of Users Solution for timestamps of events which aren’t

synchronised

ModelMy Events User 1’s Events

My Shared Event User 1’s Shared Event

Shared Event

Thank you