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Journal ArticleDOI

Efficient Parallel Framework for HEVC Motion Estimation on Many-Core Processors

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TLDR
This paper analyzes the ME structure in HEVC and proposes a parallel framework to decouple ME for different partitions on many-core processors and achieves more than 30 and 40 times speedup for 1920 × 1080 and 2560 × 1600 video sequences, respectively.
Abstract
High Efficiency Video Coding (HEVC) provides superior coding efficiency than previous video coding standards at the cost of increasing encoding complexity. The complexity increase of motion estimation (ME) procedure is rather significant, especially when considering the complicated partitioning structure of HEVC. To fully exploit the coding efficiency brought by HEVC requires a huge amount of computations. In this paper, we analyze the ME structure in HEVC and propose a parallel framework to decouple ME for different partitions on many-core processors. Based on local parallel method (LPM), we first use the directed acyclic graph (DAG)-based order to parallelize coding tree units (CTUs) and adopt improved LPM (ILPM) within each CTU (DAGILPM), which exploits the CTU-level and prediction unit (PU)-level parallelism. Then, we find that there exist completely independent PUs (CIPUs) and partially independent PUs (PIPUs). When the degree of parallelism (DP) is smaller than the maximum DP of DAGILPM, we process the CIPUs and PIPUs, which further increases the DP. The data dependencies and coding efficiency stay the same as LPM. Experiments show that on a 64-core system, compared with serial execution, our proposed scheme achieves more than 30 and 40 times speedup for 1920 × 1080 and 2560 × 1600 video sequences, respectively.

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Citations
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Spectral clustering steered low-rank representation for subspace segmentation

TL;DR: A spectral clustering steered LRR representation algorithm which combines the objection functions of Ncut, K-means and LRR together is proposed which is able to find low-rank affinity matrices which are most beneficial for Ncut to get best segmentation results.
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Homogeneity-based fast CU partitioning algorithm for HEVC intra coding

TL;DR: Experimental results confirm that the proposed approach can reduce up to 41% of encoding time in average for different video classes and can reach up to 58% for high homogenous texture video sequences.
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Robust head pose estimation based on key frames for human-machine interaction

TL;DR: A head pose estimation framework that combines 2D and 3D cues using the concept of key frames (KFs) that can handle partial occlusions and extreme rotations even with noisy depth data, improving the accuracy of pose estimation and detection rate.
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Unpaved road detection based on spatial fuzzy clustering algorithm

TL;DR: A novel algorithm is proposed to improve the accuracy and robustness of unpaved road detection and boundary extraction with low computational costs and can achieve better performance than some state-of-the-art methods in terms of detection accuracy and speed.
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Understanding human activities in videos: A joint action and interaction learning approach

TL;DR: Both the features learned via deep nets and human interaction context are leveraged to encode the correlations among actions and pairwise interactions in a structured model, and all model parameters are trained via a large-margin framework.
References
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Book

The Design and Analysis of Computer Algorithms

TL;DR: This text introduces the basic data structures and programming techniques often used in efficient algorithms, and covers use of lists, push-down stacks, queues, trees, and graphs.
Journal ArticleDOI

Overview of the High Efficiency Video Coding (HEVC) Standard

TL;DR: The main goal of the HEVC standardization effort is to enable significantly improved compression performance relative to existing standards-in the range of 50% bit-rate reduction for equal perceptual video quality.
Journal ArticleDOI

Scope of validity of PSNR in image/video quality assessment

TL;DR: Experimental data are presented that clearly demonstrate the scope of application of peak signal-to-noise ratio (PSNR) as a video quality metric and it is shown that as long as the video content and the codec type are not changed, PSNR is a valid quality measure.
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