Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31824
Content-based Indoor/Outdoor Video Classification System for a Mobile Platform

Authors: Mitko Veta, Tomislav Kartalov, Zoran Ivanovski


Organization of video databases is becoming difficult task as the amount of video content increases. Video classification based on the content of videos can significantly increase the speed of tasks such as browsing and searching for a particular video in a database. In this paper, a content-based videos classification system for the classes indoor and outdoor is presented. The system is intended to be used on a mobile platform with modest resources. The algorithm makes use of the temporal redundancy in videos, which allows using an uncomplicated classification model while still achieving reasonable accuracy. The training and evaluation was done on a video database of 443 videos downloaded from a video sharing service. A total accuracy of 87.36% was achieved.

Keywords: Indoor/outdoor, video classification, imageclassification

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1391


[1] J.Stauder, J.Sirot, H. Le Borgne, E. Cooke, N.E.O'Connor "Relating visual and semantic image descriptors", Proceedings of European Workshop for the Integration of Knowledge, Semantic and Digital Media Technologies, EWIMT 2004, London, UK, November 25-26, 2004
[2] M. Szummer and R.W. Picard, "Indoor-outdoor image classification,"1998 IEEE International Workshop on Content-Based Access of Image and Video Database, 1998. Proceedings., 1998, pp. 42- 51.
[3] N. Serrano, A.E. Savakis, and J. Luo, "Improved scene classification using efficient low-level features and semantic cues,"Pattern Recognition, vol. 37, 2004, pp. 1773-1784.
[4] A. Payne and S. Singh, "Indoor vs. outdoor scene classification in digital photographs" Pattern Recognition, vol. 38, 2005, pp. 1533-1545.
[5] R. Schettini, C. Brambilla, C. Cusano, and G. Ciocca, "Automatic classification of digital photographs based on decision forests."
[5] A. Payne and S. Singh, "Indoor vs. outdoor scene classification in digital photographs,"Pattern Recognition, vol. 38, 2005, pp. 1533-1545.
[6] S. Bianco, G. Ciocca, C. Cusano, and R. Schettini, "Improving Color Constancy Using Indoor-Outdoor Image Classification,"Image Processing, IEEE Transactions on, vol. 17, 2008, pp. 2381-2392.
[7] A. Vailaya, M.A.T. Figueiredo, A.K. Jain, H.J. Zhang, A. Technol, and P. Alto, "Image classification for content-based indexing,"IEEE Transactions on Image Processing, vol. 10, 2001, pp. 117-130.
[8] A. Miene, T. Hermes, G. Ioannidis, R. Fathi, and O. Herzog, "Automatic shot boundary detection and classification of indoor and outdoor scenes," NIST SPECIAL PUBLICATION SP, 2003, pp. 615-620.
[9] Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines, 2001. Software available at