David Crandall
Abstract
This article describes our work in using online photo collections to reconstruct information about the world and its inhabitants at both global and local scales. This work has been driven by the dramatic growth of social content-sharing Web sites, which have created immense online collections of user-generated visual data. Flickr.com alone currently hosts more than 6 billion images taken by more than 40 million unique users, while Facebook.com has said it grows by nearly 250 million photos every day.
- Agarwal, S., Snavely, N., Simon, I., Seitz, S., Szeliski, R. 2009. Building Rome in a day. International Conference on Computer Vision.Google Scholar
Cross Ref
- The App Garden. 2010; http://www.flickr.com/services/api/.Google Scholar
- Building Rome in a day; http://grail.cs.washington.edu/projects/rome/.Google Scholar
- Chen, X., Morvan, Y., He, Y., Dorsey, J., Rushmeier, H. 2010. An integrated image and sketching environment for archaeological sites. Workshop on Applications of Computer Vision in Archaeology.Google ScholarCross Ref
- Comaniciu, D., Meer, P. 2002. Mean shift: a robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(5). Google ScholarDigital Library
- Crandall, D., Backstrom, L., Cosley, D., Suri, S., Huttenlocher, D., Kleinberg, J. 2010. Inferring social ties from geographic coincidences. Proceedings of the National Academy of Science 107(52):22436-22441.Google ScholarCross Ref
- Crandall, D., Backstrom, L., Huttenlocher, D., Kleinberg, J. 2009. Mapping the world's photos. International World Wide Web Conference. Google ScholarDigital Library
- Crandall, D., Backstrom, L., Huttenlocher, D., Kleinberg, J. Mapping the world's photos; http:// www.cs.cornell.edu/~crandall/photomap/. Google ScholarDigital Library
- Crandall, D., Owens, A., Snavely, N., Huttenlocher, D. 2011. Discrete-continuous optimization for large-scale structure from motion. Conference on Computer Vision and Pattern Recognition: 3001-3008. Google ScholarDigital Library
- Crandall, D., Owens, A., Snavely, N., Huttenlocher, D. 2011. Discrete-continuous optimization for large-scale structure from motion; http://vision.soic.indiana.edu/disco/. Google ScholarDigital Library
- Flickr. 2011. 6,000,000,000; http://blog.flickr.net/en/2011/08/04/6000000000/.Google Scholar
- Hartley, R., Zisserman, A. 2003. Multiple View Geometry in Computer Vision. Cambridge: Cambridge University Press. Google ScholarDigital Library
- Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., Van Alstyne, M. 2009. Computational social science. Science 323(5915):721-723.Google ScholarCross Ref
- Lowe, D. G. 2004. Distinctive image features from scale-invariant keypoints. International Journal in Computer Vision. Google ScholarDigital Library
- Melki, S. Photo reproduced under a Creative-Commons-Attribution license. Flickr user sergemelki; http://www.flickr.com/photos/sergemelki/3391168464/in/photostream/.Google Scholar
- Michel, J.-B., Shen, Y. K., Aiden, A. P., Veres, A., Gray, M. K., The Google Books Team, Pickett, J. P., Hoiberg, D., Clancy, D., Norvig, P., Orwant, J., Pinker, S., Nowak, M., Lieberman-Aiden, E. 2011. Quantitative analysis of culture using millions of digitized books. Science 331(6014):176-182.Google ScholarCross Ref
- Milgram, S. 1976. Psychological Maps of Paris. In Environmental Psychology: People and Their Physical Settings, ed. H. M. Proshansky, W. H. Ittelson, and L. G. Rivlin, 104-124. New York: Holt, Rinehart and Winston.Google Scholar
- Pearl, J. 1988. Probabilistic reasoning in intelligent systems: networks of plausible inference. San Mateo, California: Morgan Kaufmann Publishers. Google ScholarDigital Library
- Photo Tourism; http://phototour.cs.washington.edu/.Google Scholar
- Shaffer, J. 2011. Bigger, faster photos. The Facebook Blog; http://blog.facebook.com/blog.php?post=10150262684247131.Google Scholar
- Snavely, N., Seitz, S., Szeliski, R. 2008. Modeling the world from Internet photo collections. International Journal of Computer Vision 80(2). Google ScholarDigital Library
- Tuite, K., Snavely, N., Hsiao, D.-Y., Tabing, N., Popovi, Z. 2011. PhotoCity: training experts at large-scale image acquisition through a competitive game. Conference on Human Factors in Computing (CHI). Google ScholarDigital Library
- Zhang, H., Korayem, M., Crandall, D., LeBuhn, G. 2012. Mining Photo-sharing Websites to Study Ecological Phenomena. International World Wide Web Conference. Google ScholarDigital Library
Index Terms
- Modeling People and Places with Internet Photo Collections: Understanding the world from the sea of online photos
Recommendations
Geo-referenced Tourist Attraction Photo Tagging by Mining Community Photo Collections
Advances in Multimedia Information Processing – PCM 2013AbstractThe advent of photo sharing sites like Flickr has drastically increased the volume of community photo collections on the web. Also the rising popularity of the mobile devices with GPS cameras like iPhone has made most of the photos geo-tagged. ...
Reviews
Alexis Leon
Advancements in digital photography and facilities for storing and sharing photos on the Internet have made digital photography accessible to millions of people. This article shares the authors' work with online photo collections to recreate information about the world and its people, using automatic algorithms that analyze photos and associated metadata such as geotags, timestamps, captions, user profiles, social contacts, and so on. These algorithms succeed at automatically identifying most photographed places; creating 3D models from 2D photographs; and discovering people's travel patterns, among other similar tasks. The authors explain how data is cleaned, how useful photos are separated from those that lack relevant information, how metadata is obtained and used, how their algorithms work, and the principles and concepts used in developing those algorithms. They also explain the limitations of available photo collections and describe techniques, such as using computer games, to motivate people to take photos that will help in recreating the world. The article concludes with a discussion of the potential uses of this technology in other fields and the need for future work to make the system foolproof and efficient. This is a must-read for people working in computer vision, pattern recognition, data mining, knowledge discovery, artificial intelligence, and related fields, as it opens a new avenue for gathering information from photo collections. This would also help scientists, engineers, meteorologists, cartographers, and professionals in related fields. The ability to create 3D models from 2D photographs and recreate the sequence of events at a particular place from photos taken over a period of time can be very useful as an investigation tool. Online Computing Reviews Service
Access critical reviews of Computing literature here
Become a reviewer for Computing Reviews.
Comments