1,720,962 research outputs found
Multiview Video Coding Accelerated on Multicore Architectures
No full textThis thesis deals with the design and implementation of extremely parallel fast motion / disparity estimation algorithm for multicore architectures. Currently, H.264/AVC is the most widely used commercial video compression standard and is based on single view. Recently, Multi-view Video Coding (MVC) has also been standardized as an extension to H.264/AVC for supporting 3D and Free Viewpoint video. As MVC is an extension to H.264/AVC, so it achieves compression not only by exploiting temporal and spatial prediction but also exploits inter-view redundancies using motion estimation tool. In H.264/AVC, motion estimation is the most important tool employed by the video encoder to mitigate temporal redundancies but it is also the most time consuming. Consequently, in MVC, the time consumed for efficient encoding is even higher as the encoder has to perform temporal as well as inter view predictions. This thesis proposes a parallel low-complexity rate-distortion optimized motion/disparity estimation algorithm that can be implemented on multicore architectures such as Graphical Processing Unit (GPU). Recently, GPU has emerged as a commercially viable multicore platform for accel-
erating computationally extensive applications and has also been applied for improving video encoder performance. Generally, the bit rate cost during motion vector calculation is ignored while implementing parallel motion estimation algorithms on GPU, due to the unavailability of the spatially predicted motion vectors, which leads to rate-distortion performance degradation. The proposed approach is able to perform the complex prediction task by means of an efficient distribution of all the computations over the GPU by mitigating the spatial dependencies. The experimental results show that the proposed scheme achieves significant speedup and has comparable rate-distortion performance with respect
to sequential fast motion estimation algorithm. The proposed algorithm is also used for exploiting inter-view prediction in MVC and is implemented on the GPU exploiting view and block level parallelism simultaneously. The results for MVC suggest a significant speedup with negligible loss in coding efficiency
N Point DCT VLSI Architecture for Emerging HEVC Standard
No full textThis work presents a flexible VLSI architecture to compute the N-point DCT. Since HEVC supports different block sizes for the computation of the DCT, that is, 4 × 4 up to 3 2 × 3 2, the design of a flexible architecture to support them helps reducing the area overhead of hardware implementations. The hardware proposed in this work is partially folded to save area and to get speed for large video sequences sizes. The proposed architecture relies on the decomposition of the DCT matrices into sparse submatrices in order to reduce the multiplications. Finally, multiplications are completely eliminated using the lifting scheme. The proposed architecture sustains real-time processing of 1080P HD video codec running at 150 MH
Parallel Rate-Distortion Optimised Fast Motion Estimation Algorithm for H.264/AVC using GPU
No full textParallel H.264/AVC Fast Rate-Distortion Optimized Motion Estimation using Graphics Processing Unit and Dedicated Hardware
Full text linkHeterogeneous systems on a single chip composed of CPU, Graphical Processing Unit (GPU), and Field Programmable Gate Array (FPGA) are expected to emerge in near future. In this context, the System on Chip (SoC) can be dynamically adapted to employ different architectures for execution of data-intensive applications. Motion estimation is one such task that can be accelerated using FPGA and GPU for high performance H.264/AVC encoder implementation. In most of works on parallel implementation of motion estimation, the bit rate cost of motion vectors is generally ignored. On the contrary, this paper presents a fast rate-distortion optimized parallel motion estimation algorithm implemented on GPU using OpenCL and FPGA/ASIC using VHDL. The predicted motion vectors are estimated from temporally preceding motion vectors and used for evaluating the bit rate cost of the motion vectors simultaneously. The experimental results show that the proposed scheme achieves significant speedup on GPU and FPGA, and has comparable ratedistortion performance with respect to sequential fast motion estimation algorith
VLSI Architecture for Low-Complexity Motion Estimation in H.264 Multiview Video Coding
No full textThis paper presents a VLSI architecture for a low complexity motion estimation algorithm, referred to as Slim264, for multiview video coding extension of H.264. Algorithmic modifications are introduced to obtain a fully parallel computational structure able to meet the throughput requirements of high resolution and high frame rate videos. High parallelism is achieved by predicting small blocks, i.e. 4x4 pixel blocks, in parallel and then adding them up in order to get Sum of Absolute Differences (SADs) of large block sizes. The predictor is able to support high resolution videos i.e. 1080p. The modified algorithm shows promising PSNR results with respect to full search algorithm. The predictor is synthesized with a clock frequency of 200 MHz, occupying an area of 0.49 mm2, on 90-nm Standard Cell ASIC technolog
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
De-identification and anonymization of protected health information
No full textWith the growing advancement of science and technology, research has become the vital step in every educational field. This research survey reflects light on the methods of de-identification and anonymization for protecting the privacy of the patients, practitioners and nurses. Huge amount of patient data is required to researchers for carrying out different analysis. Patient information must thus be preserved to maximum although privacy policies must not make the data less valuable to researchers through over sufficient data masking or by using any other de-identification technique. De-identification and anonymization techniques masks the patient identity through using various techniques such as suppression, randomization, shuffling, creating pseudonyms, generalization, adding noise, scrambling, masking, encoding, encryption etc. The dataset having critical information is called protected health information (PHI) through which an individual can be identified. Thus PHI must be preserved through any means to make data valuable as well as protecting data from hackers
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