Title :
Change Detection with Weightless Neural Networks
Author :
De Gregorio, Massimo ; Giordano, M.
Author_Institution :
Ist. di Cibernetica, E. Caianiello (ICIB), Pozzuoli, Italy
Abstract :
In this paper a pixel -- based Weightless Neural Network (WNN) method to face the problem of change detection in the field of view of a camera is proposed. The main features of the proposed method are 1) the dynamic adaptability to background change due to the WNN model adopted and 2) the introduction of pixel color histories to improve system behavior in videos characterized by (des)appearing of objects in video scene and/or sudden changes in lightning and background brightness and shape. The WNN approach is very simple and straightforward, and it gives high rank results in competition with other approaches applied to the ChangeDetection.net 2014 benchmark dataset.
Keywords :
neural nets; object detection; video signal processing; ChangeDetection.net 2014 benchmark dataset; WNN; background brightness; background change adaptability; background shape; camera field-of-view; change detection; lightning; pixel color history; pixel-based weightless neural network; video scene; Face; History; Image color analysis; Neural networks; Random access memory; Training; Videos; Change Detection; Weightless Neural Networks;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
DOI :
10.1109/CVPRW.2014.66