C.I.T.SOFTWARE Y S.MULTIMEDIA

 

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  


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  


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)

 

                                                                                                                                                                                                                             
 
                                                                   
 
                                                                                                                                                             
 
      

 

 

C.I. T.SOFTWARE Y S. MULTIMEDIA (CITSEM)

Last February 8th, the GTI received the visit of Miguel Chavarrías Lapastora, Eduardo Juárez Martínez and César Sanz Álvaro, from the Research Center on Software Technologies and Multimedia Systems for Sustainability of the Universidad Politécnica de Madrid (CITSEM).

During their visit, the GTI carried out five demonstrations on several of the research lines they are currently working on:

- Subjective evaluation tests of immersive reality (Carlos Cortés).
- Biometric facial recognition system (Marcos de Rodrigo).
- Car detection system in extreme situations (Daniel Fuertes).
- System for detecting free parking spaces (Leyre Encío).
- Gesture recognition system (Enmin Zhong).

Finally, the planning of the ongoing ANÉMONA project, of which they are part of the consortium, was discussed.

The main objectives of the national research project ANEMONA are to analyse the behaviour, breeding conditions and environmental context of fish populations. To achieve this purpose, new artificial intelligence algorithms will be developed, using non-invasive sensors such as video cameras, to analyse and infer the behaviour of different fish species. Transfer learning methods for efficient cross-species data management, selection and reuse will also be investigated. Behavioural analysis and recognition will eventually be integrated into a prototype capable of making high-level decisions that can improve breeding conditions, welfare and environmental context. The project aligns with several of the European Commission's Sustainable Development Goals: Sustainable use and protection of water and marine resources, and Protection and restoration of biodiversity and ecosystems; and is expected to have a significant scientific, technical and socio-economic impact in these areas.

More information about the project in the following link: https://blogs.upm.es/anemona/

 

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