Pablo Montero

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Motion estimation is known to be one of the most expensive tasks in video coding as it is usually performed through blind search-based methods. However, in the particular case of computer-generated video, the rendering stage provides useful information to speed up the process. In this paper, we propose a fast motion estimation algorithm, designed to run(More)
This paper studies the adaptation of one of the most popular motion estimation methods to a massively parallel environment. To achieve the performance benefits that this and other related methods exhibit in CPU, a proper use of the GPU branching capabilities is required. We prove this claim and the viability of the branching approach, and achieve(More)
Modern GPUs excel in parallel computations, so they are an interesting target to perform matrix transformations such as the DCT, a fundamental part of MPEG video coding algorithms. Considering a system to encode synthetic video (e.g., computer-generated frames), this approach becomes even more appealing, since the images to encode are already in the GPU,(More)
Fine-Grain parallelism is essential for real-time video encoding performance. This usually implies setting a fixed buffer size for each encoded block. The choice of this parameter is critical for both performance and hardware cost. In this paper we analyze the impact of buffer size on image subjective quality, and its relation with other encoding(More)
BACKGROUND Child and maternal health outcomes have notably improved in Mexico since 1990, whereas rising adult mortality rates defy traditional epidemiological transition models in which decreased death rates occur across all ages. These trends suggest Mexico is experiencing a more complex, dissonant health transition than historically observed. Enduring(More)
In recent years, the development and demand of multimedia product grows increasingly fast, contributing to insufficient bandwidth of network and storage of memory device. Therefore, the theory of data compression became more significant for reducing data redundancy to save more hardware space and transmission bandwidth. Cloud computing on the other hand;(More)
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