Multimedia Communication
{Multimedia Coding and Streaming}

I'm a Research Fellow in the V-SENSE research project at Graphics Vision Visualization (GV2) / School of Computer Science and Statistics (SCSS) at Trinity College Dublin (TCD), working with Prof. Aljosa Smolic. My research interests include Multi-view (MV), High Dynamic Range (HDR), and Omni-directional [or 360-degree Virtual Reality (VR)] video processing, compression and streaming techniques.


I received the M.Sc. (Hons.) and the Ph.D. degrees from the Centre for Vision, Speech and Signal Processing at University of Surrey, UK, in 2010 and 2015, respectively. My Ph.D. work was supervised by Ahmet Kondoz and Erhan Ekmekcioglu. Afterward, I worked as a Post-doctoral researcher with Frederic Dufaux and Giuseppe Valenzise in the Multimedia Signal Processing Lab at Telecom ParisTech Institute of Science and Technology, Paris, France. Since July 2016, I am a research fellow in the Graphics Vision and Visualisation (GV2) at Trinity College Dublin (TCD).


My research interests span as follows:

  • Multiview video
  • P2P networks
  • Omnidirectional video
  • Adaptive streaming
  • HDR video
  • Video compression
  • 3D video
  • Wireless networks


My three selected published works are available in this page. You may also check my other publications using my google scholar.

HDR Video Coding based on a temporally constrained Tone Mapping Operator

The proposed tone mapping operator (TMO) simultaneously took into account the statistical characteristics of the input frame while better preserving temporal coherence of the tone mapped video sequence, and achieve an improved coding efficiency.

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    Quality-aware adaptive delivery of multi-view video

    The effect of various adaptations of decision strategies were evaluated and, as a result, a new quality-aware adaptation method was designed. The proposed method was benefiting from layer based video coding in such a way that high quality of experience (QoE) is maintained in a cost-effective manner.

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    Adaptive 3D multi-view video streaming over P2P networks

    An adaptive multi-view video streaming over the P2P system was introduced which addressed the next generation high resolution multi-view users' experiences with auto-stereoscopic displays. The solution comprises the extraction of low-overhead supplementary metadata at the media encoding server that was distributed through the network and used by clients performing network adaptation.

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    Contact Me

    You may use the form provided below in order to contact me, or my email: ozcinarc{/at/}scss{/dot/}tcd{/dot/}ie