Percorrer por autor "Marcelino, S."
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- Efficient MV prediction for zonal search in video transcodingPublication . Marcelino, S.; Faria, S.; Assunção, P.; Moiron, S.; Ghanbari, M.This paper proposes a method to efficiently find motion vector predictions for zonal search motion re-estimation in fast video transcoders. The motion information extracted from the incoming video stream is processed to generate accurate motion vector predictions for transcoding with reduced complexity. Our results demonstrate that motion vector predictions computed by the proposed method outperform those generated by the highly efficient EPZS (Enhanced Predictive Zonal Search) algorithm in H.264/AVC transcoders. The computational complexity is reduced up to 59.6% at negligible cost in R-D performance. The proposed method can be useful in multimedia systems and applications using any type of transcoder, such as transrating and/or spatial resolution downsizing.
- Error recovery of image-based depth maps using Bézier curve fittingPublication . Marcelino, S.; Assunção, Pedro; Faria, Sergio; Soares, S.This paper proposes a method to recover lost regions in image-based depth maps used in video plus depth 3D format. This method performs depth maps reconstruction taking into account depth contours within the lost regions. This is achieved by extracting the contours and recovering their lost segments based on Bézier curve fitting, followed by spatial interpolation. The proposed method maintains contour smoothness and uses them as the boundary limits of homogeneous depth regions, which are then filled through weighted pixel interpolation. The experimental results show that the proposed method yields better synthesized images than classic spatial concealment methods, uniquely based on pixel interpolation techniques. The method presented in this paper is able to outperform the reference method, in terms of PSNR by up to 1.91dB. The subjective quality is also shown as being significantly better.
- Quality evaluation of depth map error concealment using a perceptually-aware objective metricPublication . Marcelino, S.; Faria, S.; Pepion, R.; Le Callet, P.; Soares, S.; Assunção, P.This paper presents a quality evaluation study on the performance of error concealment methods for depth maps used in multiview video-plus-depth (MVD). The research deals with the problem of decoding corrupted depth maps received from error-prone networks, where the quality of the reconstructed depth data is not always directly related to the quality of the virtual views synthesised by those maps. Even after error concealment such distortions are not particularly perceived as other known types, such as coding distortion. Thus, traditional quality metrics are not adequate to capture all the relevant features. In this work, the performance of two error concealment methods for depth maps is evaluated using a perceptually-aware objective metric. This metric is validated through subjective assessment of virtual views synthesised with concealed depth maps. Each subjective test is performed by comparing the relative quality between between two synthesised images using different error concealment methods. The perceptual impact of reconstruction in corrupted depth of MVD is evaluated under various loss rates, using several colour images and depth maps encoded at multiple quantisation steps. The achieved results reveal that the proposed objective quality metric is mostly inline with user preferences, in respect to the relative performance of each error concealment method.
- Robust decoding of MDC depth maps for enhanced 3D video over hybrid broadcasting networksPublication . Marcelino, S.; Correia, P.; Faria, Sergio; Soares, S.; Assunção, PedroThis paper addresses the problem of robust decoding of 3D video over hybrid broadcast networks, using Multiple Description Coding (MDC). Despite the fact that MDC allowsdecoding of any description even when the others are lost in the multipath network, the resulting coarsely decoded depth maps produce unacceptable distortion in synthesised views. This is particularly harmful in the case of intra-coded depth slices because of subsequent error propagation. To achieve improved quality in the virtual views synthesised from MDC depth maps received with lost descriptions, a method is proposed based on the depth geometric information extracted from the received descriptions and also from texture motion. Accurate recovery of either lost or coarsely decoded depth slices from one single description, is achieved by jointly using motion information, depth map edges and spatially neighbouring depth values. Comparing with MDC decoding without enhanced reconstruction of lost descriptions, the proposed method reaches quality gains up to 2.29dB for loss rates of 10%.