A novel architecture for parallel multi-view HEVC decoder on mobile device

Liu, Wei; Li, Jiao; Cho, Yong B.

doi:10.1186/s13640-017-0174-5

Cited by 5 publications

(5 citation statements)

References 16 publications

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“…The improved acceleration algorithm combines the changes in the characteristics of the movement of the crowd and the changes in the distribution of the population. The algorithm's detection results are accurate under different block sizes [9] The neighborhood size for solving the acceleration in the experiment was 5 × 5; (3) regarding anomaly classification, most algorithms are based on empirical thresholds. The threshold ε in this paper is mainly the continuous actual detection and analysis of different datasets; and (4) an optimal behavior determination based on an optimal threshold is applied to a given video sequence.…”

Section: Population Abnormal Behavior Detectionmentioning

confidence: 99%

Big data analytics of crime prevention and control based on image processing upon cloud computing

Xu¹,

Cheng²,

Sugumaran³

2020

JSSS

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Aim: Current crime behavior observation has the problem of not being real time, thus criminal behavior cannot be promptly controlled. To improve the control of criminal behavior, this study was based on cloud computing image processing, and adopted data mining for criminal behavior. Methods: This study obtained many criminal behavior characteristics through data collection and combined the rapid response capability of cloud computing to adopt data processing. In addition, to improve the accuracy of criminal behavior recognition, the identification method for criminal behaviors in selected populations was studied, and the image processing technology was combined to identify individual crimes and subject segmentation. Results: Our work used statistical methods to collect the characteristics of criminal behavior, and we designed experiments to verify the effectiveness of the algorithm. The experimental research shows that the algorithm has high accuracy in identifying abnormal behavior. Conclusion: The research shows that the accuracy of the algorithm for identifying abnormal behavior is relatively high, and it has high practical value, which can meet the accuracy and real-time requirements of security systems.

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Section: Population Abnormal Behavior Detectionmentioning

confidence: 99%

Big data analytics of crime prevention and control based on image processing upon cloud computing

Xu¹,

Cheng²,

Sugumaran³

2020

JSSS

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“…This method was able to minimize the decoding time by 30% compared to the sequential method. Other embedded implementation of HEVC decoder that applies a parallel optimized method was reported by Liu et al [14] for the multi-view video decoding using the multi-threading. The results show that the proposed method is 5 times faster in the ARM platforms.…”

Section: Related Workmentioning

confidence: 99%

A New Optimized Implementation of a Fast Intra Prediction Mode Decision Algorithm for Hevc Standard

Touzani¹,

Wali²,

Errahimi³

et al. 2020

IJC

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New and stronger video compression standard was developed during the last years, called H.265/HEVC (High Efficiency Video Coding). This standard has undergone several improvements compared to H.264/AVC (Advanced Video Coding). In intra prediction block, 33 directional intra prediction modes were included in H.265 to have an efficient coding instead of 8 modes that were used in H.264 in addition to planar and DC modes, which has generated computational complexities in the new standard. Therefore one of the most issues for embedded implementation of HEVC is time reduction of the encoding process. In this paper, an embedded implementation of a fast intra prediction algorithm is performed on ARM processors under the embedded Linux Operating System. Experimental results included the comparison between the original HM16.7 and the proposed algorithm show that the encoding time was reduced by an average of 61.5% with an increase of 1.19 in the bit rate and a small degradation in the PSNR of 0.05%.

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“…In [16], an optimized method for MV-HEVC is proposed. It uses multi-threading and SIMD instructions implementation on ARM processors.…”

Section: Related Workmentioning

confidence: 99%

“…Stage 3: Filtering, which corresponds to transitions (15,16,17,18,19,20,21,22,23,24,25,26). This stage corresponds to the Loop Filter process A parametric analysis of the application has enabled to deduce that the overall execution time of Stages 0, 1 and 3 is approximately equivalent to the execution time of Stage 2.…”

Section: Pipeline Execution Approachmentioning

confidence: 99%