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Even though the latest video compression techniques such as High Efficiency Video coding (HEVC) have succeeded in significantly alleviating the bandwidth consumption during high resolution video transmission, they have become severely susceptible to transmission errors. Overcoming the resulting temporal impact of the transmission errors on the decoded video requires efficient error resilient schemes that can introduce robustness features to the coded video in order to mitigate the negative impact on the viewer. To this end, this paper proposes a rate-controlled error resilient bit allocation scheme, together with an encoding parameter selection process, to adaptively determine the most robust video coding parameters and the decoder error concealment operations during the encoding itself. Consequently, the proposed method has demonstrated 0.48dB-0.62dB PSNR gain over the state-of-the art methods at the same bit rate.

Social interaction of groups of users, amongst themselves and with the media content itself, is increasingly becoming popular due to the advancements in the Internet access technologies. However, multimedia resource provisioning for dispersed user groups poses a challenge and demands innovative technologies. This paper proposes a novel approach based on Particle Swarm Optimization (PSO) to optimally allocate computational and networking resources to a group of interactive users, such that the group Quality-of-Service (QoS) is maximized. We evaluate the performance of the proposed improved PSO method with respect to the state-of-the-art greedy resource allocation mechanisms and related PSO approaches. The ability to find a feasible solution (i.e., the serving probability) and the accuracy of such solutions are compared for different network topologies. The proposed method demonstrates reduced computational complexity, an up to 40% increase in the serving probability compared to the greedy methods, and up to 60 times faster convergence compared to the basic PSO approach. Overall, the comparable QoS level to the optimal solution suggests that the proposed solution efficiently allocates the resources available in the network.

Though ubiquitous, the full potential of consumer electronic devices in the home, as content creators, remains underutilized due to the limited interaction between the consumers and the existing on-demand application and media services. Although services such as interactive television could change this, the geographic distribution of groups of consumers and the need for on-the-fly media processing that this entails, makes the efficient utilization of resources a complex optimization task requiring mechanisms to simultaneously allocate processing and network resources to groups of users. However, these technologies have not yet been developed, and brute force methods remain prohibitively complex. In order to overcome this problem, this paper proposes heuristic algorithms to both generate end-to-end delay bound multicast trees for individual groups of users and to co-locate multiple multicast trees, such that a minimum group quality metric can be satisfied. The performance of the proposed heuristic solution is evaluated in terms of the serving probability, i.e., the resource utilization efficiency, and computation time of the resource allocation decision making process. Simulation results show that improvements in the serving probability of up to 50%, in comparison with existing generic resource allocation schemes, and several orders of magnitude reduction of the computation time, in comparison to an optimal linear programming solution approach, can be achieved.

New algorithms are being investigated in the context of next generation video coding to achieve higher compression efficiency. In particular, intra block copy is well known to accurately predict screen content and artificially generated content where patterns and edges may repeat within the frame. On the other hand, such type of video content is often subject to geometrical transformations such as transitions, rotations, zooms etc, which may not be accurately captured by simply copying neighbouring pixels. A new intra-prediction scheme is presented in this paper whereby blocks of samples from already reconstructed areas are processed by means of an affine-type transformation. This allows more accurate prediction of blocks which improve compression efficiency in a variety of conditions. Experiments in the context of Versatile Video Coding standard show the proposed method can improve intra-coding compression efficiency by 2.01% BD-rates on average, and up to 4.81%, with negligible impact on the decoder complexity.