SPECIAL SESSION #26
Video quality assessment for feature detection and augmented reality
ORGANIZED BY
Valerio De Luca
Valerio De Luca
AVR Lab, Department of Engineering for Innovation, University of Salento
ABSTRACT
The identification of distinctive features in a video and their tracking within consecutive frames is the basis for the implementation of image-based augmented reality systems. Their effectiveness also depends on the quality of the video, which is determined by the codec and encoding parameters but can be partially altered by packet losses and jitter in the case of video streaming. Various metrics often inspired by the human visual system have been introduced to assess video quality. This special session aims to gather studies that analyse video quality with the specific aim of assessing whether they are suitable for feature detection and tracking.
MAIN TOPICS
Topics of interest include, but are not limited to, the following:
- Video quality metrics
- Effects of packet loss and jitter
- Feature detection
- Feature tracking
- Performance evaluation
- Errors in detection and tracking
- Error measurement methods
- Error prediction methods
- Evaluation of image artefacts
- GPU-based optimization
- Adaptive streaming
- Network-based optimization
- AI-based techniques
ABOUT THE ORGANIZERS
Valerio De Luca graduated magna cum laude from the University of Salento in Computer Engineering in 2009 and received a Ph.D. in Information Engineering from the same university in 2014. He is currently an Assistant Professor at the Department of Engineering for Innovation at the University of Salento. His past research interests include grid computing, distributed systems for real-time audio-video streaming and QoE. Since 2015, he works with the Augmented and Virtual Reality Laboratory (AVR Lab), where he is involved in projects on human-computer interaction and extended reality for medicine, education, cultural heritage. He recently w orked also on GPU computing, with application to optimal UAV path planning, and on augmented reality for improvement of situation awareness in UAV remote control. Since 2022, he has been working on an extended reality project for preoperative planning and intraoperative support in orthopaedic surgery.
