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Tracking of moving targets in video sequences

Academic Article
Publication Date:
2005
abstract:
A research has been carried out finalised to the definition of a methodology useful to detect and track moving targets in video sequences. Algorithms performing this task have been also developed for real time monitoring and surveillance purposes. Due to deformations occurring in the appearance of the target in the videos, a Hierarchical Artificial Neural Network (HANN) has been used to recognize target occlusion or masking, and to increase the normal tracking performance. Preliminary results are presented regarding both identification and tracking of animal moving at night in an open environment, and the surveillance of known scenes for unauthorized access control.
Iris type:
01.01 Articolo in rivista
Keywords:
Applications; Scene Analysis; Segmentation; Implementation; Object recognition; Image Processing; Target tracking; Hierarchical Artificial Neural Networks
List of contributors:
DI BONO, MARIA GRAZIA; Benvenuti, Marco; Pieri, Gabriele; Colantonio, Sara; Salvetti, Ovidio
Authors of the University:
COLANTONIO SARA
PIERI GABRIELE
Handle:
https://iris.cnr.it/handle/20.500.14243/79634
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/79634/143714/prod_68321-doc_125859.pdf
Published in:
WSEAS TRANSACTIONS ON SYSTEMS
Journal
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