TY  - JOUR
AU  - Ariel Amato
AU  - Mikhail Mozerov
AU  - Xavier Roca
AU  - Jordi Gonzalez
PY  - 2010//
TI  - Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns
T2  - EURASIPJ
JO  - EURASIP Journal on Advances in Signal Processing
SP  - 7
N2  - Article ID 901205This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications.
SN  - 1110-8657
L1  - http://refbase.cvc.uab.es/files/AMR2010.pdf
UR  - http://dx.doi.org/10.1155/2010/901205
N1  - ISE
ID  - Ariel Amato2010
ER  -