Andrew C. Gallagher
Liangliang Cao
Jiebo Luo
ABSTRACT
In this paper, we introduce the idea of using the context of a personal calendar for labeling photo collections. Calendar event annotations are matched to images based on image capture time, and a Naïve Bayes model considers features from the calendar events as well as from computer vision-based image analysis to determine if the image actually matches the calendar event. This approach has the benefit that it requires no extra annotation from the consumer, since most people already keep calendars. In our test collections, 36% of personal images could be tagged with a label from a personal calendar. Note that our preliminary results represent a lower bound on the performance that is possible because all the system components are expected to improve over time. As people migrate toward digital calendars, we can also expect more consistency in their calendar labels, which should improve the annotation accuracy.
- Cao, L., Luo, J., Kautz H. and Huang, T. Annotating Collections of Photos Using Hierarchical Event and Scene Models, In Proc CVPR, 2008.Google Scholar
- Dalal, N. and Triggs, B., Histograms of Oriented Gradients for Human Detection, In Proc. CVPR, 2005. Google ScholarDigital Library
- Jones, M. and Viola, P., Fast Multiview Face Detector, In Proc. CVPR, 2003.Google Scholar
- Loui, A. and A. Savakis. Automated Event Clustering and Quality Screening of Consumer Pictures for Digital Albuming, IEEE Trans. Multimedia, 5(3): 390--402, 2003. Google ScholarDigital Library
- Naaman, M. Leveraging Geo-Referenced Digital Photographs, Ph.D. Dissertation, Stanford University, 2005. Google ScholarDigital Library
- Neustaedter, C. Domestic Awareness and the Role of Family Calendars, Ph.D. Dissertation, University of Calgary, 2007. Google ScholarDigital Library
- U.S. Social Security Administration. Baby Name Database. http://www.socialsecurity.gov/OACT/babynames/.Google Scholar
- http://en.wikipedia.org/wiki/Likert_scaleGoogle Scholar
Index Terms
- Image annotation using personal calendars as context
Recommendations
Automatic image annotation using semi-supervised generative modeling
Image annotation approaches need an annotated dataset to learn a model for the relation between images and words. Unfortunately, preparing a labeled dataset is highly time consuming and expensive. In this work, we describe the development of an ...
Effective image annotation for searches using multilevel semantics
There is an increasing need for automatic image annotation tools to enable effective image searching in digital libraries. In this paper, we present a novel probabilistic model for image annotation based on content-based image retrieval techniques and ...
Scalable search-based image annotation of personal images
MIR '06: Proceedings of the 8th ACM international workshop on Multimedia information retrievalWith the prevalence of digital cameras, more and more people have considerable digital images on their personal devices. As a result, there are increasing needs to effectively search these personal images. Automatic image annotation may serve the goal, ...
Comments