A novel method for efficient indoor-outdoor image classification

Journal of Signal Processing Systems

Volumn 61, Issue 3, 2010, Pages 251-258

  Kim, Wonjun ^a   Park, Jimin ^a   Kim, Changick ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

Edge and color orientation histogram; Indoor outdoor classification; Low level features; SVM classifier

Indexed keywords

DESCRIPTORS; FALSE POSITIVE; FEATURE VECTORS; INDOOR-OUTDOOR CLASSIFICATION; LOW-LEVEL FEATURES; NOVEL METHODS; ORIENTATION HISTOGRAMS; OUTDOOR SCENES; SVM CLASSIFIERS;

CLASSIFIERS; GRAPHIC METHODS; IMAGE ANALYSIS;

COLOR;

EID: 77957989802     PISSN: 19398018     EISSN: 19398115     Source Type: Journal    
DOI: 10.1007/s11265-009-0446-0     Document Type: Article

References (17)

1. Zhang, L., Mingjing, L., Hong-Jing, Z. (2002). Boosting image orientation detection with indoor vs. outdoor classification. IEEE Workshop on Applications of Computer Vision (WACV 2002), Orlando, FL, pp. 95-99.
2. S Bianco G Ciocca C Cusano R Schettini 2008 Improving color constancy using indoor-outdoor image classification IEEE Transactions on Image Processing 17 12 2381 2392 10.1109/TIP.2008.2006661 2517440
3. Szummer, M., Picard, R., W. (1998). Indoor-outdoor image classification. IEEE Workshop on Content-Based Access of Image and Video Database, Bombay, India, pp. 42-51.
4. Y Ohta T Kanade T Sakai 1980 Color information for region segmentation Computer Graphics and Image Processing 13 222 241 10.1016/0146-664X(80)90047-7
5. Serrano, N., Savakis, A., Luo, J. (2002). A computationally efficient approach to indoor/outdoor scene classification. International Conference on Pattern Recognition (ICPR), QC, Canada, 4, pp. 146-149.
6. L Gupta, et al. 2007 Indoor versus outdoor scene classification using probabilistic neural network EURASIP Journal on Advances in Signal Processing 1 123 133
7. A Payne S Singh 2005 Indoor vs. outdoor scene classification in digital photographs Pattern Recognition 38 10 1533 1545 10.1016/j.patcog.2004.12.014 (Pubitemid 41037091)
8. Luo, J., Savakis, A. (2001). Indoor vs. outdoor classification of consumer photographs using low-level and semantic features. International Conference on Image Processing (ICIP), Thessaloniki, Greece, vol. 2, pp. 745-748.
9. Boutell, M., Luo, J. (2004). Bayesian fusion of camera metadata cues in semantic scene classification. Computer Vision and Pattern Recognition (CVPR), Washington, D.C., vol. 2, pp. 623-630.
10. Boutell, M., Choudhury, A., Luo, J., Brown, C., M. (2006). Using semantic features for scene classification: how good do they need to be ?. International Conference on Multimedia and Expo (ICME), Toronto, Canada, pp. 785-788.
11. A Vailaya M Figueiredo AK Jain H-J Zhang 2001 Image classification for content-based indexing IEEE Transactions on Image Processing 10 1 117 130 1061.68580 10.1109/83.892448 (Pubitemid 32136886)
12. Spyrou, E., Mylonas, P., Avrithis, Y. (2008). Using region semantics and visual context for scene classification. International Conference on Image Processing (ICIP), San Diego, CA, pp. 53-56.
13. W Kim C Kim 2009 An efficient indoor-outdoor scene classification method Journal of the Institute of Electronics Engineers of Korea 46-SP 5 48 55
14. CJ Burges 1998 A tutorial on support vector machines for pattern recognition Data Mining and Knowledge Discovery 2 121 167 10.1023/A: 1009715923555 (Pubitemid 128126769)
15. Y-T Chen C-S Chen 2008 Fast human detection using a novel boosted cascading structure with meta stages IEEE Transactions on Image Processing 17 8 1452 1464 10.1109/TIP.2008.926152 2516912
16. Dalal, N., Triggs, B. (2005). Histograms of oriented gradients for human detection. Computer Vision and Pattern Recognition (CVPR), San Diego, CA, vol. 1, pp. 886-893.
17. Gonzalez, R. C., & Woods, R. E. (2002). Digital image processing. Upper Saddle River: Prentice-Hall.