ACM Home Page
Please provide us with feedback. Feedback
Automatic organization for digital photographs with geographic coordinates
Full text PdfPdf (381 KB)
Source International Conference on Digital Libraries archive
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries table of contents
Tuscon, AZ, USA
SESSION: Geographic aspects of digital libraries table of contents
Pages: 53 - 62  
Year of Publication: 2004
ISBN:1-58113-832-6
Authors
Mor Naaman  Stanford University
Yee Jiun Song  Stanford University
Andreas Paepcke  Stanford University
Hector Garcia-Molina  Stanford University
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 18,   Downloads (12 Months): 191,   Citation Count: 39
Additional Information:

abstract   references   cited by   index terms   review   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/996350.996366
What is a DOI?

ABSTRACT

We describe PhotoCompas, a system that utilizes the time and location information embedded in digital photographs to automatically organize a personal photo collection PhotoCompas produces browseable location and event hierarchies for the collection. These hierarchies are created using algorithms that interleave time and location to produce an organization that mimics the way people think about their photo collections. In addition, our algorithm annotates the generated hierarchy with geographical names. We tested our approach in case studies of three real--world collections and verified that the results are meaningful and useful for the collection owners.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
2
3
 
4
U. Gargi, Consumer media capture: Time-based analysis and event clustering Technical Report HPL-2003--165, HP Laboratories, August 2003.
5
 
6
Google inc http://www.google.com
7
8
 
9
L. L. Hill, J. Frew, and Q. Zheng Geographic names - the implementation of a gazetteer in a georeferenced digital library CNRI D-Lib Magazine, January 1999.
10
 
11
A. Loui and A. E. Savakis Automatic image event segmentation and quality screening for albuming applications. In IEEE International Conference on Multimedia and Expo, 2000.
 
12
M. Naaman, S. Harada, Q. Wang, and A. Paepcke Adventures in space and time: Browsing personal collections of geo--referenced digital photographs Technical report, Stanford University, April 2004 Submitted for Publication.
 
13
M. Naaman, A. Paepcke, and H. Garcia-Molina From where to what: Metadata sharing for digital photographs with geographic coordinates. In 10th International Conference on Cooperative Information Systems (CoopIS), 2003.
 
14
 
15
J. C. Platt, M., and B. A. Field Phototoc: Automatic clustering for browsing personal photographs Technical Report MSR-TR-2002--17, Microsoft Research, February 2002.
16
 
17
G. Schwarz Estimating the dimension of a model. The Annals of Statistic, 6:461--464, 1978.
 
18
19
 
20
W. Wagenaar My memory: A study of autobiographical memory over six years Cognitive psychology, 18:225--252, 1986.
21

CITED BY  39


REVIEW

"Michael Lesk : Reviewer"

Given a set of photographs labeled with both geographic location and time, this paper explains how to cluster the photographs, and then name the clusters. The goal is to select short and recognizable geographic names, and to do this, the presented  more...

Collaborative Colleagues:
Mor Naaman: colleagues
Yee Jiun Song: colleagues
Andreas Paepcke: colleagues
Hector Garcia-Molina: colleagues