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  • No-reference lightweight estimation of 3D video objective quality
    Publication . Soares, João R. S.; Cruz, Luis A. da Silva; Assunção, Pedro; Marinheiro, Rui
    A no-reference (NR) method based on an artificial neural network (ANN) approach is proposed in this paper to estimate the objective quality of video-plus-depth streams subject to packet loss in depth data. A novel aspect of this method is the use of information only taken from packet headers, up to the network abstraction layer (NAL), requiring a very low complexity parsing of the compressed video streams. A maximum of seven packet-layer parameters were found to be enough to provide accurate objective quality estimates given by the structural similarity index (SSIM). The accuracy of the quality estimates, evaluated by comparison with the actual SSIM quality scores, is shown to be sufficiently high (e.g., Pearson Linear Correlation Coefficient over 0.92) for lightweight implementations of 3D video quality monitors at end-user receivers and also at network nodes.
    2014-10-27Comunicação em conferência Acesso restrito Ver mais
  • Selective motion vector redundancies for improved error resilience in HEVC
    Publication . Carreira, J.; Ekmekcioglu, E; Kondoz, A.; Assuncao, P.; Faria, S.; Silva, V. De
    This paper addresses the problem caused by motion vector coding dependencies on the error resilience performance of the emergent High Efficiency Video Coding (HEVC) standard. We propose a method based on the prediction dependency of motion vectors (MV) to select the most relevant ones for redundant coding with reduced overhead. The spatial dependencies are analysed in the encoder to prioritise the MVs that should be selected for redundancy, based on the number of subsequent dependent coding units. Then, a subset of prioritised MVs is transmitted as redundancy (referred to as side information in the paper), to reduce the use and propagation of mismatched MV predictions in case of transmission errors or data loss. The simulation results show that the proposed MV selection method can effectively identify the most relevant motion field, achieving improved error robustness with a reduced redundancy overhead. Exploiting only 30% of the generated MVs for redundancy, average quality gains of up to 1 dB are achieved compared to a uniform MV selection scheme, and up to 2 dB compared to the original HEVC standard with no redundant encoded information.
    2014-10-27Comunicação em conferência Acesso aberto Ver mais