Articolo in rivista, 2014, ENG, 10.1016/j.cviu.2013.11.006
Maddalena, Lucia; Petrosino, Alfredo
Consiglio Nazionale delle Ricerche (CNR); Univ Naples Parthenope
We propose the 3dSOBS+ algorithm, a newly designed approach for moving object detection based on a neural background model automatically generated by a self-organizing method. The algorithm is able to accurately handle scenes containing moving backgrounds, gradual illumination variations, and shadows cast by moving objects, and is robust against false detections for different types of videos taken with stationary cameras. Experimental results and comparisons conducted on the Background Models Challenge benchmark dataset demonstrate the improvements achieved by the proposed algorithm, that compares well with the state-of-the-art methods. (C) 2013 Elsevier Inc. All rights reserved.
Computer vision and image understanding (Print) 122 , pp. 65–73
Background subtraction, Motion detection, Neural network, Self organization
ID: 282398
Year: 2014
Type: Articolo in rivista
Creation: 2014-07-21 10:52:59.000
Last update: 2016-03-01 12:25:54.000
CNR authors
CNR institutes
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:282398
DOI: 10.1016/j.cviu.2013.11.006
ISI Web of Science (WOS): 000334394900006
Scopus: 2-s2.0-84898079786