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VSQuAD 2022

VSQuAD: Video Surveillance Quality Assessment Dataset     —————————————————————————–

VSQuAD – Video Surveillance Quality Assessment Dataset

Copyright(c) 2022 – All Rights Reserved.

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Permission to use, copy, or modify this database and its documentation for educational and research purposes only and without fee is hereby granted, provided that this copyright notice and the original authors’ names appear on all copies and supporting documentation.This database shall not be used, redistributed, or adapted as the basis of a commercial softwareor hardware product without first obtaining permission of the authors. The authors make no representations about the suitability of this database for any purpose. It is provided « as is » without express or implied warranty.

VsQUAD link:  https://www.l2ti.univ-paris13.fr/VSQuad/

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Investigators:

The main investigators of the work are:

Leader :

  • Azeddine Beghdadi, University Sorbonne Paris Nord, France

Co-PIs

  • Mounir Kaaniche, Borhen-eddine Dakkar ; L2TI lab, University Sorbonne Paris Nord, France
  • -Muhammad Ali Qureshi, Hammad Hassan Gillani; The Islamia University of Bahawalpur
  • (Pakistan),
  • - Zohaib Amjad Khan; L2S, CentraleSupélec, University Paris Saclay, France
  • - Faouzi Alaya Cheikh, Mohib Ullah; Norwegian University of Science and Technology,
  • Norway,

How to cite the database:

The associated paper containing more details and analysis has been accepted in ICIP 2022.

Title « A new video quality assessment dataset for video surveillance applications »

Authors : Azeddine Beghdadi, Muhammad Ali Qureshi, Borhen-eddine Dakkar, Hammad Hassan Gillani, Zohaib Amjad Khan, Mounir Kaaniche, Mohib Ullah, Faouzi Alaya Cheikh; in the IEEE  proceedings of ICIP2022, 16-19 October 2022, Bordeaux, France

Download (PDF)

Contacts:

● Prof. Azeddine Beghdadi, L2TI, Université Sorbonne Paris Nord, France

beghdadi@sorbonne-paris-nord.fr

● Muhammad Ali Qureshi, The Islamia University of Bahawalpur, Pakistan

ali.qureshi@iub.edu.pk

● Borhen-eddine Dakkar

dakkarborheneddine@gmail.com

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Below are the details on the VSQuAD dataset

Please contact at beghdadi@sorbonne-paris-nord.fr , if you have any questions.

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Laparoscopic Video Quality (LVQ) Database (link below) — 2018–

https://drive.google.com/file/d/1SoONeacp9vvihTY7zmWssG_cnVzx16oq/view

Laparoscopic Video Quality Database (LVQ) contains 10 reference laparoscopic videos each of 10 seconds duration which are distorted with 5 different distortions at 4 different levels. The distortions include some of those often encountered during the laparoscopic surgery namely defocus blur, motion blur, uneven illumination, smoke and noise. The subjective scores in the database were obtained both from non-medical observers (29 in total) as well as medical observers (9 in total).

Lead Principal Investigator (LPI)  : Azeddine Beghdadi

Co-PIs : Khan, Z.A., , Cheikh, F.A., Kaaniche, M., Pelanis, E., Palomar, R., Fretland, Å.A., Edwin, B. and Elle, O.J

This database is made available for strictly research-oriented use. Please refer to the following articles:

  1. Khan, Z.A., Beghdadi, A., Cheikh, F.A., Kaaniche, M., Pelanis, E., Palomar, R., Fretland, Å.A., Edwin, B. and Elle, O.J., 2020, March. Towards a video quality assessment based framework for enhancement of laparoscopic videos. In Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment (Vol. 11316, p. 113160P). International Society for Optics and Photonics.
  2. Z. A. Khan, A. Beghdadi, F. Alaya-Cheikh, M. Kaaniche, « Residual Networks based Distortion Classification and Ranking for Laparoscopic Image quality Assessment », IEEE- ICIP2020, Abu Dhabi, UEA, 25-28 October 2020

CEED2016 : Contrast Enhancement Evaluation Database , Mendeley Data v2, 2017.

The associated database we developed can be downloaded from Mendeley datasets. 

https://dx.doi.org/10.17632/3hfzp6vwkm.2

Lead Principal Investigator (LPI)  : Azeddine Beghdadi

Co-PI : Muhammad Qureshi, Bilel Sdiri, Mohamed Deriche, Faouzi Alaya-Cheikh

This database is made available for strictly research-oriented use. Please refer to the following papers:

  1. A. Beghdadi, M. A. Qureshi, B. Sdiri, M. Deriche, F. Alaya Cheikh, « CEED – A Database for Image Contrast Enhancement Evaluation. CVCS 2018: 1-6, September 19-20, 2018, Gjøvik, Norway,(PDF)
  2. Muhammad Ali Qureshi, Azeddine Beghdadi, and Mohamed Deriche, « Towards the design of a consistent image contrast enhancement evaluation measure », Signal Processing: Image Communication, Elsevier, Volume 58, Part C, 14 August 2017, pp.212-227,  DOI: 10.1016/j.image.2017.08.004, http://www.sciencedirect.com/science/article/pii/S0923596517301431
  3. M. Qureshi, A. Beghdadi, B. Sdiri, M. Deriche, F. A. Cheikh, A Comprehensive Performance Evaluation of Objective Quality Metrics For Contrast Enhancement Techniques, in: European Workshop on Visual Information Processing (EUVIP), Marseille, France, 25-27 October 2016, pp. 1–5, http://dx.doi.org/10.1109/EUVIP.2016.7764589
  4. A. Beghdadi, M. Ali Qureshi, M. Deriche, « A critical look at some contrast enhancement evaluation measures », IEEE – CVCS2015, Gjovik, Norway, :August 25-26, 2015, http://ieeexplore.ieee.org/document/7274888/

We appreciate your feedback on both the papers and the database.

Acknowledgment
People who have contributed to this database:

Bilel Sdiri, Borhen Eddine Dakkar, Lynda Chami, Asjad Amin, Ashiq Hussain and the 23 participants . Thanks to Shaohua Chen who provided the matlab code of MRETINEX..

VQUAD

Open dataset for video quality assessment in the context of video-surveillance

VQUAD is  dataset dedicated to video quality assessment in the context of video surveillance. This database consists of a set of common distortions at different levels of annoyance. The subjective tests are performed using a classical pair comparison protocol with some new configurations.

This new database referred to as VQUAD, contains 14 color full-HD (1920,1080 pixels) videos and 224 distorted videos. The database is built with free-use youtube videos from live streams and some common videos used by the video processing community from Virat Database. Youtube videos are provided by a video surveillance equipment’s provider from Netherlands called WebCam.NL.

Database link: https://data.mendeley.com/datasets/f9xd5zp8mp/1

Lead Principal Investigator (LPI)  : Azeddine Beghdadi

Co-PIs : I. Bezzine, Z. A. Khan, N. Almaadeed, M. Kaaniche, S. Almaadeed, A. Bouridane, F. Alaya Cheikh

Citations : I. Bezzine, Z. A. Khan, A. Beghdadi, N. Almaadeed, M. Kaaniche, S. Almaadeed, A. Bouridane, F. Alaya Cheikh, »Video quality assessment dataset for smart public security systems », in the proceedings of the 23rd International IEEE – INMIC2020, Bahawalpur, Pakistan, 5-7 November 2020,

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Free Image Processing and Analysis  software

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MRETINEX

« Natural Enhancement of Color Image » by S. Chen, A. Beghdadi, —  Code and demo available at http://www.ipol.im/pub/pre/252/. —–  details are published in  Eurasip Journal on Image and Video Processing, Volume 2010 (2010), Article ID 175203, 19 pages,doi:10.1155/2010/175203, PDF

TRAITIM

Traitim : Some image processing tools (low-level treatments) developed with my colleague and friend Alain Le Négrate.

The details of some methods developed in this software are published in :

  1. A. Beghdadi, A. Le Négrate, P. Viaris De Lesegno.,  » Entropic thresholding using a block source model  » , Computer Vision Graphics and Image Processing : Graphical Models and Image Processing, Vol.57, N°.3, May, pp.197-205, 1995
  2. A. Le Négrate, A. Beghdadi and H. Dupoisot., « An Image Enhancement Technique and its Evaluation through Bimodality Analysis « , Computer Vision Graphics and Image Processing : Graphical Models and Image Processing, Vol. 54, N°. 1, Jan. 1991, 13-22.
  3. A. Beghdadi, A. Le Négrate. » Contrast Enhancement Technique Based on the Local Detection of Edges « , Computer Vision Graphics and Image Processing, 46, 1989, 162-174.
  4. A. Beghdadi, A. Constans, P. Gadenne, J. Lafait,  » Optimum Image Processing for Morphological Study of Granular Thin Films « , Rev. Phys. Appl., Jan. 1986, 73-80

 SMARTFLOW

Smartflow : displacement field estimation and some image processing tools developed with my former PhD student Jérôme Monteil

The details of some methods developed in this software are published in :

  1. A. Beghdadi, M. Mesbah, J. Monteil, « A Fast Incremental Approach for Accurate Measurement of the Displacement Field « , Image and Vision Computing Journal, 21, (2003), pp.383-399 (PDF)
  2. J. Monteil, A. Beghdadi,  » A New Interpretation and improvement of the Nonlinear Anisotropic Diffusion for Image Enhancement « , IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, N°9,1999, 940-946. (PDF)
  3. A. Beghdadi, M.-F. Auclair-Fortier and J. Monteil, « Tracking of Image Intensities Based on Optical Flow : An Evaluation of Nonlinear Diffusion Process », Proceedings of the 2nd IEEE International Symposium on Signal Processing and Information Technology, pp.691-696, Marrakesh, Morocco, 18-21 December 2002.
  4. J. Monteil, A. Beghdadi,  » A new adaptive nonlinear anisotropic diffusion for noise smoothing « , Procedings of IEEE International Conference on Image Processing, Chicago October 1998, Vol. 3, pp. 254-258  (PDF)
  5. N. Ben Amar, A. Beghdadi and P. Viaris De Lesegno,  » An All-Digital Method for Accurate Measurements of Mechanical Deformations « , Scanning, The Journal of Scanning Microscopy, Vol.18, 3, (1996),pp.327-330.
  6. J. Monteil, A. Beghdadi, P. Viaris de Lesegno, « Mesure du champ de déformation par une technique incrémentale de flux optique »- la Revue de Métallurgie – CIT , tome 97, N°.2, février 2000, pp.229-238.

 

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