RT Conference Proceedings
T1 Vehicle Classification in Traffic Environments Using the Growing Neural Gas
A1 Molina-Cabello, Miguel Ángel
A1 Luque-Baena, Rafael Marcos
A1 López-Rubio, Ezequiel
A1 Ortiz-de-Lazcano-Lobato, Juan Miguel
A1 Domínguez-Merino, Enrique
A1 Muñoz Pérez, José
K1 Redes neuronales (Informática)
AB Traffic monitoring is one of the most popular applications of automated video surveillance. Classification of the vehicles into types is important in order to provide the human traffic controllers with updated information about the characteristics of the traffic flow, which facilitates their decision making process. In this work, a video surveillance system is proposed to carry out such classification. First of all, a feature extraction process is carried out to obtain the most significant features of the detected vehicles. After that, a set of Growing Neural Gas neural networks is employed to determine their types. A qualitative and quantitative assessment of the proposal is carried out on a set of benchmark traffic video sequences, with favorable results.
PB Springer
YR 2017
FD 2017
LK http://hdl.handle.net/10630/13945
UL http://hdl.handle.net/10630/13945
LA eng
NO I. Rojas et al. (Eds.): IWANN 2017, Part II, LNCS 10306, pp. 225–234, 2017. DOI: 10.1007/978-3-319-59147-6 20
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 25 ene 2026