At the KiVS 2009 conference, I received the Master Thesis Award from the communication in distributed systems (KuVS) group for my thesis entitled Statistical Error Model to Impair an H.264 Decoder. See a copy of the award here and retrieve the slides of my talk here. Please find below some pictures of the award session, taken by KiVS organisers.

Me giving the talk.

Professor Lars Wolf, head of the award comitee, ceremoniously presented the KuVS award to me.

I’m leaving for KiVS’09 (conference on communication in distributed systems), where I will give a talk entitled “Stochastic Packet Loss Model to Evaluate QoE Impairments” in the award session (I will receive the master thesis award from the communication in distributed systems group). Although there is a paper deadline approaching, I hope to have a little blog coverage on the conference.

I’ll give a talk entitled Statistical Error Model to Impair an H.264 Decoder tomorrow at Deutsche Telekom Laboratories / Berlin Institute of Technology. Further information can be found here.

Abstract:

Real-time Internet services are gaining in popularity due to rapid provisioning of broadband access technologies. Delivery of high Quality of Experience (QoE) is important for consumer acceptance of multimedia applications.
IP packet level errors affect QoE and the resulting quality degradations have to be taken into account in network operation. This talk shows how second order statistics of the number of packet losses in finite Markov models over several relevant time-scales can be derived and used to adapt models to the loss process visible in traffic measurements in wired and wireless networks.

Markov models obtained in this way provide a generator for packet loss pattern to be used in the estimation of the degradation in the Quality of Experience QoE) for Internet services, especially real-time video streams.

The evaluation of statistical properties of video streams impaired by Markov models generating packet loss shows shows different error pattern at the application (video) layer depending on the used parameter estimation method. This finding highlights the need for models replicating error pattern which are relevant for higher layers.