Smart transportation and mobility solutions
Mentor: Roberto Javier López Sastre
Email: robertoj.lopez@uah.es
Phone: (+34) 918856720
University: Universidad de Alcalá
Partner Host Institution: N.A
Keywords: computer vision, artificial intelligence, deep learning, smart transportation, Object counting, crowd counting

Smart transportation and mobility solutions

The main objective of this line of research is to apply the most advanced techniques in artificial intelligence and computer vision to address the development of new intelligent transport and mobility solutions. In particular, we will address the problem of advanced vehicle detection and counting approaches for the problems of: a) smart routing; and b) prediction and management of traffic congestions;

Departament: Signal Theory and Communications
Research Group: GRAM
More Information: http://agamenon.tsc.uah.es/Investigacion/gram/
http://agamenon.tsc.uah.es/Personales/rlopez/
Relevants projects on the area: Project 1: DGT 2014 - Accurate count of vehicles for situations of high congestion in traffic surveillance images URL: http://agamenon.tsc.uah.es/Investigacion/gram/projects/dgt2014/index.html
Project 2: STIMULO (IPT-2012-0808-370000) http://agamenon.tsc.uah.es/Investigacion/gram/projects/stimulo/index.html
Relevants publications on the area: 1.- Towards perspective-free object counting with deep learning. Daniel Oñoro-Rubio and R. J. López-Sastre. ECCV 2016
2.- The challenge of simultaneous object detection and pose estimation: a comparative study Daniel Oñoro-Rubio, Roberto J. López-Sastre, Carolina Redondo-Cabrera, Pedro Gil-Jiménez. IMAVIS, 2018.