Browsing by Author "Soares, Salviano"
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- Digital sound processing using arduino and MATLABPublication . Silva, Sergio; Soares, Salviano; Valente, Antonio; Marcelino, Sylvain T.Over the last decade, impelled by the huge open source software community support, the low cost Arduino platform presents itself as an alternative for digital sound processing. Although Arduino is generally used for small applications for the artistic and maker community, its built-in Analog to digital converter can be used for sound capturing, processing and reproduction. Equipped with a powerful AVR 8 bit RISC microcontroller, the Arduino, can achieve up to 200kHz with a 10 bit resolution according to the Atmel ATmega328P datasheet that is the AVR core that we are going to focus on this article. Realizing the hardware potential, software suppliers like Matworks or National instruments, have included the Arduino packages on the software accessories of MATLAB and LABView. This work presents some of the sound capabilities and specific limitations of the Arduino platform, enfacing its connection and installation with MATLAB software. A series of examples of the Arduino interface with MATLAB are detail and shown in order to facilitate users initiation of MATLAB and Arduino Digital Sound Processing enhancing education fostering.
- Optimal voice packet classification for enhanced VoIP over priority-enabled networksPublication . Neves, Filipe; Soares, Salviano; Assunção, PedroThis paper proposes a method for optimal classification of voice packets to enhance the quality of voice communications over priority-enabled networks when poor transmission conditions occur. Either high or low priority is assigned to each packet according to the relevance of its payload (voice segment) for the voice intelligibility. Then, in case of constrained networking conditions, by discarding first the voice packets of lower importance, the network always delivers those segments that most contribute to the perceptual quality. The proposed method is based on a dynamic programming optimisation algorithm that finds the optimal subset of m high priority voice segments in each utterance of size n > m. Such optimal subset minimizes the reconstruction distortion over all possible subsets with the same size m (i.e., the distortion incurred by a utterance reconstructed from only m segments). The simulation results show that the proposed method consistently achieves higher mean opinion scores (MOS) in comparison with non-selective packet drop under the same random network loss conditions, yielding better quality of experience (QoE) for the same packet loss rates (PLR). The priority classification algorithm is independent from error concealment methods and distortion metrics used in the optimisation process, which allows generalisation for diverse communication networks and applications.
- Reconstruction of lost depth data in multiview video-plus-depth communications using geometric transformsPublication . Marcelino, Sylvain; Soares, Salviano; Faria, Sergio; Assunção, PedroThis paper addresses depth data recovery in multiview video-plus-depth communications affected by transmission errors and/or packet loss. The novel aspects of the proposed method rely on the use of geometric transforms and warping vectors, capable of capturing complex motion and view-dependent deformations, which are not efficiently handled by traditional motion and/or disparity compensation methods. By exploiting the geometric nature of depth information, a region matching approach combined with depth contour reconstruction is devised to achieve accurate interpolation of arbitrary shapes within lost regions of depth maps. The simulation results show that, for different packet loss rates, up to 20%, the depth maps recovered by the proposed method produce virtual views with better quality than existing methods based on motion information and spatial interpolation. An average PSNR gain of 1.48 dB is obtained in virtual views synthesised from depth maps using the proposed method.