RT Journal Article
T1 Panorama Construction for PTZ Camera Surveillance with the Neural Gas network
A1 Thurnhofer-Hemsi, Karl
A1 López-Rubio, Ezequiel
A1 Domínguez-Merino, Enrique
A1 Luque-Baena, Rafael Marcos
A1 Molina-Cabello, Miguel Ángel
A2 Thurnhofer-Hemsi, Karl
K1 Videovigilancia
AB The construction of a model of the background of a scene still remains as a challenging task in video surveillance systems, in particular for moving cameras. This work presents a novel approach for constructing a panoramic background model based on the neural gas network and a subsequent piecewise linear interpolation by Delaunay triangulation. Furthermore, an ensemble model of neural gas networks is also proposed. The approach can handle arbitrary camera directions and zooms for a pan-tilt-zoom camera-based surveillance system. After testing the proposed approach on several indoor sequences, the results demonstrate that the proposed methods are effective and suitable to use for real-time video surveillance applications.
PB Wiley
YR 2018
FD 2018-04
LK https://hdl.handle.net/10630/32808
UL https://hdl.handle.net/10630/32808
LA eng
NO Thurnhofer‐Hemsi, K., López‐Rubio, E., Domínguez, E., Luque‐Baena, R. M., & Molina‐Cabello, M. A. (2018). Panorama construction for PTZ camera surveillance with the neural gas network. Expert Systems, 35(2), e12249.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026