A new video segmentation method of moving objects based on blob-level knowledge

Author:

Carmona Enrique J.,Martínez-Cantos Javier,Mira José

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference22 articles.

1. Carmona, E.J., Martínez-Cantos, J., Mira, J. 2006. Posprocesamiento morfológico adaptativo basado en algoritmos genéticos y orientado a la detección robusta de humanos. Campus Multidisciplinary in Perception and Intelligence, CMPI-2006, 10–14 July 2006, Albacete (Spain), pp. 249–261.

2. Collins, R., Lipton, A., Kanade, T., Fujiyoshi, H., Duggins, D., Tsin, Y., Tolliver, D., Enomoto, N., Hasegawa, O., 2000. A System for Video Surveillance and Monitoring: VSAM Final Report. Technical Report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University.

3. Detecting moving objects, ghost and shadows in video streams;Cucchiara;IEEE Trans. Pattern Anal. Machine Intell.,2003

4. Dedeoglu, Y., 2004. Moving Object Detection, Tracking and Classification for Smart Video Surveillance. PhD Thesis, Department of Computer Engineering and The Institute of Engineering and Science of Bilkent University.

5. Length–speed ratio (LSR) as a characteristic for moving elements real-time classification;Fernández;Real-Time Imaging,2003

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