End of Master Project

 

Research  

 

GTI Data   

 

Open databases created and software developed by the GTI and supplemental material to papers.  

 

Databases  

SportCLIP (2025): Multi-sport dataset for text-guided video summarization.
Ficosa (2024): The FNTVD dataset has been generated using the Ficosa's recording car.
MATDAT (2023):  More than 90K labeled images of martial arts tricking.
SEAW – DATASET (2022): 3 stereoscopic contents in 4K resolution at 30 fps.
UPM-GTI-Face dataset (2022): 11 different subjects captured in 4K, under 2 scenarios, and 2 face mask conditions.
LaSoDa (2022): 60 annotated images from soccer matches in five stadiums with different characteristics and light conditions.
PIROPO Database (2021):People in Indoor ROoms with Perspective and Omnidirectional cameras.
EVENT-CLASS (2021): High-quality 360-degree videos in the context of tele-education.
Parking Lot Occupancy Database (2020)
Nighttime Vehicle Detection database (NVD) (2019)
Hand gesture dataset (2019): Multi-modal Leap Motion dataset for Hand Gesture Recognition.
ViCoCoS-3D (2016): VideoConference Common Scenes in 3D.
LASIESTA database (2016): More than 20 sequences to test moving object detection and tracking algorithms.
Hand gesture database (2015): Hand-gesture database composed by high-resolution color images acquired with the Senz3D sensor.
HRRFaceD database (2014):Face database composed by high resolution images acquired with Microsoft Kinect 2 (second generation).
Lab database (2012): Set of 6 sequences to test moving object detection strategies.
Vehicle image database (2012): More than 7000 images of vehicles and roads.           

 

Software  

NaviFormer (2025): A Deep Reinforcement Learning Transformer-like Model to Holistically Solve the Navigation Problem.
Empowering Computer Vision in Higher Education(2024): A Novel Tool for Enhancing Video Coding Comprehension.
Engaging students in audiovisual coding through interactive MATLAB GUIs (2024)
TOP-Former: A Multi-Agent Transformer Approach for the Team Orienteering Problem (2023)
Solving Routing Problems for Multiple Cooperative Unmanned Aerial Vehicles using Transformer Networks (2023)
Vision Transformers and Traditional Convolutional Neural Networks for Face Recognition Tasks (2023)
Faster GSAC-DNN (2023): A Deep Learning Approach to Nighttime Vehicle Detection Using a Fast Grid of Spatial Aware Classifiers.
SETForSeQ (2020): Subjective Evaluation Tool for Foreground Segmentation Quality. 
SMV Player for Oculus Rift (2016)
Bag-D3P (2016): Face recognition using depth information. 
TSLAB (2015): Tool for Semiautomatic LABeling.    

   

Supplementary material  

Viewpoint-Invariant Soccer Pitch Registration Using Geometric and Learned Features (2025)
Soccer line mark segmentation and classification with stochastic watershed transform (2022)
A fully automatic method for segmentation of soccer playing fields (2022)
Grass band detection in soccer images for improved image registration (2022)
Evaluating the Influence of the HMD, Usability, and Fatigue in 360VR Video Quality Assessments (2020)
Automatic soccer field of play registration (2020)   
Augmented reality tool for the situational awareness improvement of UAV operators (2017)
Detection of static moving objects using multiple nonparametric background-foreground models on a Finite State Machine (2015)
Real-time nonparametric background subtraction with tracking-based foreground update (2015)  
Camera localization using trajectories and maps (2014)

 

                                                                                                                                                                                                                             
 
                                                                   
 
                                                                                                                                                             
 
      

 

 

Design and development of an immersive training tool for people with intellectual disability

Martina Merolli presents her End of Master Project (TFM) on immersive training for people with intellectual disabilities

Researcher and master's student at the Grupo de Tratamiento de Imágenes (GTI), Martina Merolli, presented her TFM on Thursday, February 20, 2025, titled: "Design and development of an immersive training tool for people with intellectual disability".

With a grade of 9.5, this innovative project focuses on the design and development of an immersive training tool based on Virtual Reality (VR), aiming to improve the cognitive, work, and autonomy skills of people with intellectual disabilities.

An innovative approach with Virtual Reality

People with intellectual disabilities face challenges in developing cognitive and social skills, as well as in their integration into the workforce. To address these difficulties, Martina Merolli's project proposes the use of simulated virtual environments, such as a supermarket and a restaurant, where users can practice and improve skills related to memory, attention, and autonomy in a safe and interactive setting.

Additionally, the system incorporates biomarkers such as eye-tracking, head movements, and heart rate to analyze emotions and anxiety levels, providing valuable information for improving cognitive therapy.

Evaluation and user testing

The project has been developed with an experimental and applied approach, including user testing at the Juan XXIII Foundation, where key data was collected to assess the tool’s effectiveness. Measurements of cognitive performance were carried out using sensors and questionnaires, with a special focus on improving memory and attention.

A step forward in job inclusion

The development of immersive training tools based on Virtual Reality opens new possibilities for the job inclusion of people with intellectual disabilities. The ability to train in simulated environments and adjust the difficulty of activities allows for personalized experiences that facilitate learning and integration into the labor market.

From GTI, we congratulate Martina Merolli on this outstanding work and her contribution to research in accessibility and inclusion. Congratulations!

 

MartinaTFM