Bachelor's projects 2012/2013
Apply for a Bachelor's project at the Universidad Rey Juan Carlos official website 
- Project 1: "Face verification in fast crossing border systems".
Number of vacancies: 3.
Degrees: Degree in Information Technology Engineering.
Observations: This project studies several representations and classification techniques for identity verification in a border control system using real images. We have a database acquired at Madrid Barajas airport. The real images taken at the control post will be used to define a training kernel for a one-class SVM. We will compare the performance of different classifiers. The aim is to find the ideal representation, which should be robust enough to work in real time.
Responsible professor: Enrique Cabello Pardos, PhD. - Project 2: "Bio-inspired vision systems".
Number of vacancies: 3.
Degrees: Degree in Information Technology Engineering.
Observations: This project studies several vision representations and techniques for movement detection by means on bio-inspired systems.
Responsible professor: Enrique Cabello Pardos, PhD. - Project 3: "Intelligent video surveillance systems".
Number of vacancies: 3.
Degrees: Degree in Information Technology Engineering, Degree in Computer Engineering, Degree in Software Engineering.
Observations: This project is about the design and development of intelligent video surveillance systems applied to airport scenarios and other infrastructures. We have real database from an airport camera system.
Responsible professor: Cristina Conde Vilda, PhD. - Project 4: "Bio-inspired vision systems".
Number of vacancies: 3.
Degrees: Degree in Information Technology Engineering, Degree in Computer Engineering, Degree in Software Engineering.
Observations: This project is about the development of biologically-inspired information processing systems, which will be applied to real problems. We have an artificial retina for the event-based acquisition of information.
Responsible professor: Cristina Conde Vilda, PhD. - Project 5: "Face authentication".
Number of vacancies: 2.
Degrees: Degree in Information Technology Engineering.
Observations: This project studies several representation and classification techniques for identity verification in an access control system by means of real images. We have a database a database adquired at Madrid Barajas airport. The real images taken at the control will be used to define a training kernel for a one-class SVM. We will compare the performance of different classifiers. We aim to find the ideal representation, robust enough for working in real time.
Responsible professor: Isaac Martín de Diego, PhD. - Project 6: "Visual representation of the way of driving".
Number of vacancies: 1.
Degrees: Degree in Information Technology Engineering.
Observations: In this project we aim to represent the driver's behaviour by means of a finite state machine. We have several databases acquired in driving simulators. We have to define the different driving states as a function of the driving risk. The variables in the transitions between states have also to be defined, as well as the most adequate visual representation for the correct interpretation of the results in a driving session.
Responsible professor: Isaac Martín de Diego, PhD. - Project 7: "Multiple Kernel Learning for Face Recognition".
Number of vacancies: 1.
Degrees: Degree in Information Technology Engineering.
Observations: In this project we aim to compare the different kernel learning techniques for support vector machines, applied to face recognition. The techniques to compare are to be defined. They will have to be programmed in the most appropriate language. The databases needed for training these techniques have to chosen.
Responsible professor: Isaac Martín de Diego, PhD. - Project 8: "Fusion of information for risk detection for drivers".
Number of vacancies:: 2.
Degrees: Degree in Information Technology Engineering.
Observations: By means of the assessment of driving risk by a group of experts about some driving exercises taken in several simulators, we aim to learn which variables from the vehicle, the road and the driver are the most influent for risk prediction. We have several databases. The student will have to process the information from these databases as well as to program the adequate classifiers to learn the existing relationship between the covariables of interest and the driving risk. The final goal is to generate an alert system for drving able to predict potential risky situations.
Responsible professor: Isaac Martín de Diego, PhD.