Bayesian fusion of camera metadata cues in semantic scene classification

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 2, Issue , 2004, Pages

  Boutell, Matthew ^a   Luo, Jiebo ^b  

^a University of Rochester   (United States)

^b EASTMAN KODAK COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APERTURE; BAYESIAN FUSION; LOW LEVEL VISION; SEMANTIC CLASSIFIACTION;

CAMERAS; COMPUTER VISION; IMAGE CODING; LEARNING SYSTEMS; METADATA; PATTERN RECOGNITION; PROBABILITY; STATISTICAL METHODS;

SEMANTICS;

EID: 5044231131     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. M. Boutell, J. Luo, and Robert T. Gray. Sunset scene classification using simulated image recomposition. Proceedings of International Conference on Multimedia and Expo, Baltimore, MD, 2003.
2. C. Carson, S. Belongie, H. Greenspan, and J. Malik. Blobworld: Image segmentation using expectation-maximization and its application to image querying. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(8): 1026-1040, 2002.
3. nd Edition. John Wiley and Sons, Inc., New York, 2001.
4. A. Hauptmann and M. Smith. Text, speech, and vision for video segmentation: The infomedia project. Proceedings of AAAI Symposium on Computational Models for Integrating Language and Vision, 1995.
5. P. Lipson, E. Grimson, and P. Sinha, "Configuration based scene classification and image indexing," Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1997.
6. C. Liu and H.-Y. Shum. Kullback-Leibler Boosting. Proceedings of International Conference on Computer Vision and Pattern Recognition, 2003.
7. Y. Lu, C. Hu, X. Zhu, H. J. Zhang, and Q. Yang. A unified framework for semantics and feature based relevance feedback in image retrieval systems. ACM Multimedia Conference, Los Angeles, CA, 2000.
8. A. Oliva and A. Torralba. Modeling the shape of the scene: a holistic representation of the spatial envelope. International Journal of Computer Vision, 42(3): 145-175, 2001.
9. S. Paek and S.-F. Chang. A knowledge engineering approach for image classification based on probabilistic reasoning systems. Proceedings of IEEE International Conference on Multimedia and Expo, 2000.
10. J. Platt. AutoAlbum: Clustering digital photographs using probabilistic model merging. IEEE Workshop on Content-based Access of Image and Video Libraries, 2000.
11. R. Segur, "Using photographic space to improve the evaluation of consumer cameras," Proceedings of IS&T Image Processing, Image Quality, Image Capture and Systems (PICS) Conference, 2000.
12. N. Serrano, A. Savakis and J. Luo. A Computationally Efficient Approach to Indoor/Outdoor Scene Classification. Proceedings of International Conference on Pattern Recognition, 2002.
13. J. R. Smith and C.-S. Li. Image classification and querying using composite region templates. Journal of Computer Vision and Image Understanding, 75(1/2):165-174, 1999.
14. Y. Song and A. Zhang. Analyzing scenery images by monotonic tree. ACM Multimedia Systems Journal, 2002.
15. Z. Sun, "On Multiple Cue Integration", Proceedings of International Conference on Computer Vision and Pattern Recognition, 2003.
16. M. Szummer and R. W. Picard. Indoor-outdoor image classification. Proceedings of IEEE Workshop on Content-based Access of Image and Video Databases, 1998.
17. D. Tax and R. Duin. Using two-class classifiers for multi-class classification. International Conference on Pattern Recognition, Quebec City, QC, Canada, August 2002.
18. A. Vailaya, M. Figueiredo, A. Jain, and H.-J. Zhang. Content-based hierarchical classification of vacation images. Proceedings of IEEE Multimedia Systems '99 (International Conference on Multimedia Computing and Systems), Florence, Italy, 1999.