An experimental evaluation of foreground detection algorithms in real scenes

Eurasip Journal on Advances in Signal Processing

Volumn 2010, Issue , 2010, Pages

  Conte, Donatello ^a   Foggia, Pasquale ^a   Percannella, Gennaro ^a   Tufano, Francesco ^a   Vento, Mario ^a  

^a UNIVERSITY OF SALERNO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; EFFECTIVE SOLUTION; EXPERIMENTAL EVALUATION; FOREGROUND DETECTION; QUANTITATIVE MEASURES; REAL SCENES; RELIABLE ASSESSMENT; VIDEO ANALYSIS;

ALGORITHMS;

EID: 77955299972     PISSN: 16876172     EISSN: 16876180     Source Type: Journal    
DOI: 10.1155/2010/373941     Document Type: Article

References (18)

1. Li L., Leung M. K. H., Integrating intensity and texture differences for robust change detection IEEE Transactions on Image Processing 2002 11 2 105 112
2. Aach T., Kaup A., Mester R., Statistical model-based change detection in moving video Signal Processing 1993 31 2 165 180
3. Archetti F., Manfredotti C., Messina V., Sorrenti D., Foreground-to-ghost discrimination in single-difference preprocessing Proceedings of the International Conference on Advanced Concepts for Intelligent Vision Systems 2006
4. Xia J., Wu J., Zhai H., Cui Z., Moving vehicle tracking based on double difference and camshift Proceedings of the International Symposium on Information Processing 2009
5. Collins R., Lipton A., Kanade T., A system for video surveillance and monitoring May 2000 CMU-RI-TR-00-12 Pittsburgh, Pa, USA Robotics Institute
6. Horn B. K. P., Schunck B. G., Determining optical flow Artificial Intelligence 1981 17 13 185 204
7. Toyama K., Krumm J., Brumitt B., Meyers B., Wallflower: principles and practice of background maintenance 1 Proceedings of the 7th IEEE International Conference on Computer Vision (ICCV '99) September 1999 255 261
8. Conte D., Foggia P., Petretta M., Tufano F., Vento M., Meeting the application requirements of intelligent video surveillance systems in moving object detection 3687 Proceedings of the 3rd International Conference on Advances in Pattern Recognition and Image Analysis 2005 Bath, UK Springer 653 662 Lecture Notes in Computer Science
9. Wren C. R., Azarbayejani A., Darrell T., Pentland A. P., Pfinder: real-time tracking of the human body IEEE Transactions on Pattern Analysis and Machine Intelligence 1997 19 7 780 785
10. Haritaoglu I., Harwood D., Davis L. S., W4: real-time surveillance of people and their activities IEEE Transactions on Pattern Analysis and Machine Intelligence 2000 22 8 809 830
11. Stauffer C., Grimson W. E. L., Learning patterns of activity using real-time tracking IEEE Transactions on Pattern Analysis and Machine Intelligence 2000 22 8 747 757
12. Kaewtrakulpong P., Bowden R., An improved adaptive background mixture model for realtime tracking with shadow detection Proceedings of the 2nd European Workshop on Advanced Video Based Surveillance Systems (AVBS '01) 2001
13. Elgammal A., Duraiswami R., Harwood D., Davis L. S., Background and foreground modeling using nonparametric kernel density estimation for visual surveillance Proceedings of the IEEE 2002 90 7 1151 1162
14. Kim K., Chalidabhongse T. H., Harwood D., Davis L., Real-time foreground-background segmentation using codebook model Real-Time Imaging 2005 11 3 172 185
15. ulibrk D., Marques O., Socek D., Kalva H., Furht B., Neural network approach to background modeling for video object segmentation IEEE Transactions on Neural Networks 2007 18 6 1614 1627
16. Maddalena L., Petrosino A., A self-organizing approach to background subtraction for visual surveillance applications IEEE Transactions on Image Processing 2008 17 7 1168 1177
17. Li L., Huang W., Gu I. Y. H., Tian Q., Foreground object detection from videos containing complex background Proceedings of the 11th ACM International Conference on Multimedia (MM '03) November 2003 2 10
18. University of SalernoLab. of Intelligent Machines for Video, Image and Audio Analysis, Video database. http://www.adinf.unisa.it/zope/home/mivia/ databases/dbdatabase