| Title | A Perceptual Quality-driven Video Surveillance System |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Beghdadi, Azeddine, Bezzine, Ismail, Qureshi, Muhammad Ali |
| Conference Name | 2020 IEEE 23rd International Multitopic Conference (INMIC) |
| Date Published | nov |
| Keywords | distortion, distortions, Human Behavior, illumination, lighting, Measurement, Metrics, pubcrawl, quality assessment, Resiliency, security, Video quality assessment, video recording, video surveillance, visual tracking, visualization |
| Abstract | Video-based surveillance systems often suffer from poor-quality video in an uncontrolled environment. This may strongly affect the performance of high-level tasks such as visual tracking, abnormal event detection or more generally scene understanding and interpretation. This work aims to demonstrate the impact and the importance of video quality in video surveillance systems. Here, we focus on the most important challenges and difficulties related to the perceptual quality of the acquired or transmitted images/videos in uncontrolled environments. In this paper, we propose an architecture of a smart surveillance system that incorporates the perceptual quality of acquired scenes. We study the behaviour of some state-of-the-art video quality metrics on some original and distorted sequences from a dedicated surveillance dataset. Through this study, it has been shown that some of the state-of-the-art image/video quality metrics do not work in the context of video-surveillance. This study opens a new research direction to develop the video quality metrics in the context of video surveillance and also to propose a new quality-driven framework of video surveillance system. |
| DOI | 10.1109/INMIC50486.2020.9318122 |
| Citation Key | beghdadi_perceptual_2020 |
A Perceptual Quality-driven Video Surveillance System