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TU Berlin

Inhalt des Dokuments

Saman Zadtootaghaj

Lupe

Research Field
- Assessing and predicting QoE of Gaming Applications

 Research Topics

- Video quality assessment of computer generated content 

- Cloud Gaming Quality of Experience

- Deep learning-based quality assessment of image/video content

- Image/video quality enhancement  

Current Project:

Adaptive Edge/Cloud Compute and Network Continuum over a Heterogeneous Sparse Edge Infrastructure to Support Nextgen Applications (ACCORDION)

Past Project:

Methods and Models for assessing and predicting the QoE linked to Mobile Gaming (QoE-NET/MSCA-ITN Network)


Biography

Saman Zadtootaghaj is a researcher at the Quality and Usability Lab at Technische Universitat Berlin working on modeling the gaming quality of experience under the supervision of Prof. Dr.-Ing. Sebastian Moller. His main interest is subjective and objective quality assessment of Computer-Generated content. He received his bachelor degree from IASBS and master degree in information technology from University of Tehran.

He worked as a researcher at Telekom Innovation Laboratories of Deutsche Telekom AG from 2016 to 2018 as part of European project called QoE-Net. He is currently the chair of Computer-Generated Imagery group at Video Quality Expert Group.  

Roles: 

Chair of Computer-Generated Imagery (CGI) at VQEG 

Local coordinator of HCID track of EIT master program 

Visiting Researcher:

MMSPG lab, EPFL (2017)

LST group, DFKI (2019)

Teaching experience:

Advance Projects at Quality and Usability Lab (Deep Learning for Video Quality Assessment and Enhancement) SS2020

Usability engineering exercise SS2017/SS2018/SS2019/SS2020

Quality and Usability Seminar (Applied statistic) WS 2019-2020

Quality and Usability Seminar (Gamification) SS2018

Teacher assistant: Multiagent (University of Tehran 2014), computer networks (IASBS 2011).

Talks: 

VQEG meetings at Nokia, Madrid, March 2018

VQEG meetings at Google (remote), USA, November 2018 

VQEG Meetings at Deutsche Telekom, Germany, March 2019

VQEG meetings at Tencent, China, October 2019

VQEG meeting, Online Meeting, March 2020 

Involvement in Standardization Activities: 

Active in the following work items:

ITU-T P.BBQCG: Parametric bitstream-based Quality Assessment of Cloud Gaming Services

ITU-T G.CMVTQS: Computational model used as a QoE/QoS monitor to assess videotelephony services

ITU-T G.OMMOG: Opinion Model for Mobile Online Gaming applications

Contributed to the following recommendations:

ITU-T G.1032: Influence factors on gaming quality of experience  

ITU-T P.809: Subjective evaluation methods for gaming quality  

ITU-T G.1072: Opinion model predicting gaming quality of experience for cloud gaming services  

Reviewed papers for TCSVT, Quality and User Experience journal, Journal of Electronic Imaging,  QoMEX 2017-2019, ICC 2019 and ICME 2020, PQS workshop 2016

 

Tools for Quality Prediction of Gaming Content:

NDNetGaming: Deep Learning based Quality metric for Gaming Content

GamingPara: Gaming Parametric based Video Quality Models

Implementation of ITU-T Recommendation G.1072

 

Datasets:

GamingVideoSet: https://kingston.box.com/v/GamingVideoSET

Cloud Gaming Video Dataset: https://github.com/stootaghaj/CGVDS 

Image Gaming Quality Dataset: https://github.com/stootaghaj/GISET 

 

Find me on ResearchGate, LinkedIn, Scholar, GitHub.


Address
Quality and Usability Lab
Deutsche Telekom Laboratories
TU Berlin
Ernst-Reuter-Platz 7
D-10587 Berlin, Germany

Email:  
Tel:  +49 30 8353 58394

 

 

Publications:

Schmidt, Steven and Shafiee Sabet, Saeed and Zadtootaghaj, Saman and Möller, Sebastian and Griwodz, Carsten and Barman, Nabajeet and Martini, Maria G. (2019). Proposal of a Content Classification for Cloud Gaming Services. , 1–10.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian and Barman, Nabajeet and Martini, Maria G.and Shafiee Sabet, Saeed and Griwodz, Carsten (2019). Performance Evaluation of the Opinion Model Predicting Gaming QoE (G.OMG). , 1–9.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian and Barman, Nabajeet and Martini, Maria G.and Shafiee Sabet, Saeed and Griwodz, Carsten (2019). Opinion Model Predicting Gaming QoE (G.OMG). , 1–13.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian and Shafiee Sabet, Saeed (2019). Proposal for an Opinion Model Predicting Gaming QoE for Mobile Online Gaming. , 1–5.


Schmidt, Steven and Zadtootaghaj, Saman and Utke, Markus and Möller, Sebastian and Barman, Nabajeet and Martini, Maria G. and Shafiee Sabet, Saeed and Griwodz, Carsten (2019). First Draft for an Opinion Model Predicting Gaming QoE (G.OMG). , 1–21.


Avanaki, Nasim Jamshidi and Zadtootaghaj, Saman and Barman, Nabajeet and Schmidt, Steven and Martini, Maria G. and Möller, Sebastian (2020). Quality Enhancement of Gaming Content using Generative Adversarial Networks. 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 1–6.


Sabet, Saeed Shafiee and Schmidt, Steven and Zadtootaghaj, Saman and Griwodz, Carsten and Möller, Sebastian (2020). Towards the Impact of Gamers Strategy and User Inputs on the Delay Sensitivity of Cloud Games. 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 1–3.


Sabet, Saeed Shafiee and Schmidt, Steven and Zadtootaghaj, Saman and Griwodz, Carsten and Möller, Sebastian (2020). Delay Sensitivity Classification of Cloud Gaming Content. Proceedings of the 12th ACM International Workshop on Immersive Mixed and Virtual Environment Systems. Association for Computing Machinery, 25–30.


Sabet, Saeed Shafiee and Schmidt, Steven and Zadtootaghaj, Saman and Naderi, Babak and Griwodz, Carsten and Möller, Sebastian (2020). A Latency Compensation Technique Based on Game Characteristics to Mitigate the Influence of Delay on Cloud Gaming Quality of Experience. Proceedings of the 11th ACM Multimedia Systems Conference. Association for Computing Machinery, 15–25.


Schmidt, Steven and Naderi, Babak and Sabet, Saeed Shafiee and Zadtootaghaj, Saman and Carsten and Möller, Sebastian (2020). Assessing Interactive Gaming Quality of Experience using a Crowdsourcing Approach. 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 1–6.


Schmidt, Steven and Shafiee Sabet, Saeed and Naderi, Babak and Zadtootaghaj, Saman and Griwodz, Carsten and Möller, Sebastian (2020). Evaluation of Interactive Test Paradigm for P.CROWDG Recommendation. , 1–7.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian (2020). Corrigendum for ITU-T Recommendation G.1072: Opinion Model Predicting Gaming QoE. , 1–17.


Schmidt, Steven and Zadtootaghaj, Saman and Shafiee Sabet, Saeed and Möller, Sebastian (2020). Report about Opinion Model for Mobile Online Gaming Applications (G.OMMOG). , 1–9.


Zadtootaghaj, Saman and Schmidt, Steven and Möller, Sebastian and Shafiee Sabet, Saeed and Griwodz, Carsten and Barman, Nabajeet and Martini, Maria G. and Ramachandra Rao, Rakesh Rao and Göring, Steven and Raake, Alexander (2020). Proposal for new Work Item P.BBQCG: Parametric bitstream-based Quality Assessment of Cloud Gaming Services. , 1–7.


Zadtootaghaj, Saman and Schmidt, Steven and Sabet, Saeed Shafiee and Möller, Sebastian and Griwodz, Carsten (2020). Quality Estimation Models for Gaming Video Streaming Services Using Perceptual Video Quality Dimensions. Proceedings of the 11th ACM Multimedia Systems Conference. Association for Computing Machinery, 213–224.


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