2020 IEEE VR Diversity Scholarship

 

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)

 

                                                                                                                                                                                                                             
 
                                                                   
 
                                                                                                                                                             
 
      

 

 

2020 IEEE VR Diversity Scholarship

Marta Orduna, a PhD student at GTI received the 2020 IEEE VR Diversity Scholarship. The main objective of this Diversity Scholarship was to increase the diversity in the IEEE VR conference and VR Research, encouraging the participation of the underrepresented part of society that is essential in all successful research.

Due to the all-digital IEEE VR conference experience, Marta could attend on March 26th a digital luncheon for diversity scholarship recipients to network with each other. It was directed by Aleshia Hayes, John Quarles, and Mary Whitton.

The digital luncheon was a place to share experiments, points of view, and lines of research with other students and researchers in the area, enriching Marta’s thesis and giving her feedback to improve her research career. And also, why not, a place to play Bingo talking about so different topics from the favorite demo of the IEEEVR to the superpower that everyone would like to have.

marta1

marta2

Here, she wants to share 5 tips for increasing the diversity in research [*]:

5 – Replicate previous experiments but recruit underrepresented and untested populations.

4 – Collaborate more with researchers from diverse geographic locations.

3 – When reviewing papers, place more weight on population diversity.

2 – Actively recruit participants from pools outside of your university.

1 – Collect more data from your participants and report it.

[*] “diVRsify or die: Why a lack of diversity in study participants is killing VR research” - John Quarles 

Marta Orduna received the Bachelor of Engineering in Telecommunication Technologies and Services (intensification in Sound and Image) in 2016 and the Master in Telecommunication Engineering (accredited by ABET) in 2018, both from the Universidad Politécnica de Madrid (UPM), Madrid, Spain. She has been a member of the Grupo de Tratamiento de Imágenes (Image Processing Group) at the UPM since 2016. Her current research is in the area of quality, presence, and emotions in virtual reality communications. She has been involved in several projects in collaboration with Alcatel-Lucent and Nokia Bell-Labs.