VQEG (Video Quality Experts Group) - VINEDO

 

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)

 

                                                                                                                                                                                                                             
 
                                                                   
 
                                                                                                                                                             
 
      

 

 

VQEG (Video Quality Experts Group) - VINEDO

At the 2019 spring VQEG meeting in Berlin (Germany), hosted by Telekom, Narciso García presented the workplan for the analysis of the performance of objective quality metrics for immersive 360VR content. This activity extends the previously conducted analysis of the application of the well-known Video Multimethod Assessment Fusion (VMAF) metric on 360VR contents. The results proved that VMAF works sufficiently correctly with omnidirectional contents, without performing any particular adjustments.

The new challenge is to find an objective quality metric that provides high correlation with the Quality of Experience (QoE) for immersive 360VR content. Therefore, video quality, audio quality, and interaction are analyzed as essential aspects of any immersion experience. So, in addition to previous results, we are assessing the presence, the intuitive interaction, and the event-related sickness, as well as the influence of different devices.

The test material considers a wide range of contents selected with different features in terms of color, texture, camera motion, composition, and content in the scenes. The original resolution and framerate are kept throughout the process and, as video clips do not contain any scene change, there are no temporal pooling challenges.

The presence questionnaire asks for the quickness in adjusting to the virtual environment experience, the closeness to the scene objects, the awareness of events occurring in the real world, and the degree of confusion or disorientation at the beginning of breaks or at the end of the experimental session.

This activity of GTI is supported by the Spanish Projects IVME (Immersive Visual Media Environments) and VINEDO (Vídeo inmersivo para eventos distribuidos OnDemand).

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