Lost in Memories Interacting With Large Photo Collections on PDAs Susumu Harada, Mor Naaman*, Yee...
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Transcript of Lost in Memories Interacting With Large Photo Collections on PDAs Susumu Harada, Mor Naaman*, Yee...
Lost in MemoriesInteracting With Large Photo
Collections on PDAs
Susumu Harada, Mor Naaman*, Yee Jiun Song,
QianYing Wang, Andreas PaepckeDigital Library Project
Stanford University
JCDL 2004 2
Motivation
• Small devices ubiquitous
• Storage, bandwidth: cheap
• The new photo wallet: PDA/Cellphone
• Can have access to all my photos
• Co-present sharing
JCDL 2004 4
Personal Photo Collections
• Searching/browsing very difficult
• Little discernible structure to photo collections
Warning: repeat!
JCDL 2004 5
• Content-based retrieval– Basic, primitive (far from semantic)
• Manual labeling– Improved, yet cumbersome
• Visual methods for fast scanning (Zoom)– Don’t scale well, utilize unavailable screen space
Managing Personal Photos
Warning: repeat!
JCDL 2004 6
Our Approach
• Absolutely no human effort required
• Utilize automatically-captured, easy-to-get metadata, like time [and location]
Warning: repeat!
JCDL 2004 8
Outline
• Timeline Browsing– What are “Events”– Timeline user interface
• Time clustering (detecting events)
• Experiment
JCDL 2004 9
Existing PDAPhoto Browsers
• Require manual organization
• Even then, is it good enough?
JCDL 2004 10
Instead
• Use natural notion of time and event:– Photos that were taken in the same
occasion and context.
13
Timeline PDA Opening Game
Automaticallycreated
“meaningful”events
“Drill in”: Click on any box, or use timeline
JCDL 2004 20
Event Detection in Personal Collections
• Graham et al (our project). Time as essence for photo browsing through personal digital libraries. JCDL 2002.
• U. Gargi. Time-based analysis and event clustering. HP Tech Report (2003).
• Platt et al. Phototoc: Automatic clustering for browsing personal photographs. MSR Tech Report (2003).
• Stent and Loui. Using event segmentation to improve indexing of consumer photographs. SIGIR 2001.
• Cooper et al. Automatically Organizing Digital Photographs Using Time and Content IEEE Image Processing (2004).
• More…
JCDL 2004 21
Events According to Graham (et al)
Time
1 day, 11 hours
– Detect threshold gaps (6-24 hours)– Within each segment
• Find outliers• Split at outliers
– Repeat recursively
PDA: Merge at any level – limit to 10 events
10, 15, 13, 26, 400, 21, 55,…
JCDL 2004 22
Event Tree
Days
Months
Years
JCDL 2004 24
Experiment: Basic vs. Timeline
TL thumbTL time view
Basic
Timeline
• 15 subjects
• Average 1200 personal photos
JCDL 2004 25
Tasks
• Search: find randomly chosen photo in own collection as quickly as possible
• Browsing: build a collage of– Friends– Family– Trip– Special events
“Make time span and set of occasions broad”
JCDL 2004 26
The Interface or the Organization?
• Controlled using an additional condition
• Use automatic organization (events) with basic interface
JCDL 2004 27
• Even with basic interface, “automatic” matches “manual”
• After learning, Timeline improves search time by 29% over basic.
• Timeline success rate better
• Least backtracking in Timeline (after learning)
Results
JCDL 2004 28
0
10
20
30
40
50
60
70
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69
Time (seconds)
Ful l P hoto
T humbnai l
Day
Week
Month
Y ear
Time (sec)
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61
Nu
mb
er
of
Su
bje
ct-T
ria
ls 70
60
50
40
30
20
10
YearMonthWeekDayThumbsFull
View Dwelling Times
JCDL 2004 29
• At least as good as manual organization
• Novel interface beneficial
• Learning effects considerable (even better)
Conclusions
JCDL 2004 30
• Geo-photos, of course
• Utilizing “off screen space” (classify, share)
• Data collection
Current Work
JCDL 2004 32
Thank You!
More details:
Proceedings
Google: Mor Naaman
http://www-db.stanford.edu/~mor/