Low Complexity Fast Grid-Based Refining Segmentation in the V-PCC encoder

Kim, Yura; Kim, Yonghwan

doi:10.1109/icce-asia57006.2022.9954713

Cited by 7 publications

(13 citation statements)

References 3 publications

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“…This paper aims to reduce time consumption while improving RD performance and compares the proposed algorithm with TMC2-v18.0 to demonstrate its advantages. We also compare with methods from [25,26,35]. Generally, the bit rates generated by various methods do not match perfectly.…”

Section: Resultsmentioning

confidence: 99%

“…Later, Higa et al [24] proposed an optimization method to avoid unnecessary hash map access. Kim et al [25,26] used a voxel classification algorithm to improve the refining segmentation process, and, on this basis, they proposed a radius search method for the FGRS algorithm. However, it brings other problems such as a decrease in the quality of point cloud reduction.…”

Section: Related Workmentioning

confidence: 99%

“…This also reflects that our method can comprehensively consider the time and performance requirements. We compare the proposed method with [25,26,35]. As shown in Tables 10 and 11, the data from their respective papers were used for comparison.…”

Section: Comparison With Related Workmentioning

confidence: 99%

“…[25,35] compared the overall performance of their algorithms with TMC2-12.0, and ref. [26] compared the overall performance of their algorithms with TMC2-17.0. The method used in [25,26] improves the refining segmentation.…”

Section: Comparison With Related Workmentioning

confidence: 99%

“…[26] compared the overall performance of their algorithms with TMC2-17.0. The method used in [25,26] improves the refining segmentation. The fast CU decision-making method in [35] enhances the video compression process.…”

Section: Comparison With Related Workmentioning

confidence: 99%

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Improved Patch Packing and Refining Segmentation for the V-PCC Standard

Luo,

Chi,

et al. 2024

Applied Sciences

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High-performance coding solutions are urgently needed for the storage and transmission of 3D point clouds due to the development of 3D data acquisition facilities and the increasing scale of acquired point clouds. Video-based point cloud compression (V-PCC) is the most advanced international standard for compressing dynamic point clouds. However, it still has serious issues of time consumption and the large size of the occupancy map. Considering the aforementioned issues, based on V-PCC, we propose the Voxel Selection-based Refining Segmentation (VS-RS), which is used to accelerate the refining segmentation process of the point cloud. Furthermore, the data-adaptive patch packing (DAPP) is proposed to reduce the size of the occupancy map. In order to specify the effect of the improvement, we also designed novel evaluation indicators. Experimental results show that the proposed method achieves a Bjøntegaard Delta rate (BD-rate) gain of −1.58% in the V-PCC benchmark. Additionally, it reduces encoding time by up to 31.86% and reduces the size of the occupancy map by up to 20.14%.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Comparison With Related Workmentioning

confidence: 99%

Section: Comparison With Related Workmentioning

confidence: 99%

Section: Comparison With Related Workmentioning

confidence: 99%

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Improved Patch Packing and Refining Segmentation for the V-PCC Standard

Luo,

Chi,

et al. 2024

Applied Sciences

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Simple Grid-Based Refinement Segmentation Algorithm for MPEG Video-Based Point Cloud Compression

Jia,

Kim,

Lee

et al. 2024

IEEE Access

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In this paper, we proposed two simple refinement segmentation algorithms that can provide options to improve the computational complexity of the Video-based Point Cloud Compression (V-PCC) encoder. The patch image generation process in the encoding process is the most time-consuming and computationally intensive, accounting for about 70% of the encoder's self-running time in TMC2 v13.0. Since the real-time encoding of V-PCC is within the requirement of industry, it is highly necessary to research methods that can achieve good compression performance with low computational complexity. The grid-based refinement segmentation is one of the most computationally intensive processes in V-PCC. We found that the computational complexity can be reduced by further reducing the refinement segmentation process. Therefore, we propose to change the grid-based refinement segmentation loop process, thereby reducing the computational complexity by reducing some computational processes when the projection plane index of the neighboring grid point does not change. In the experiment, the compression performance of some sequences is improved by 0.1% to 0.9%, and the refinement segmentation time used is 79.21% and 79.53% of the anchor. INDEX TERMSVideo-based point cloud compression, MPEG, fast encoding, low complexity.

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Dynamic Point Cloud Compression Approach Using Hexahedron Segmentation

Tohidi,

Paul

2023

2023 IEEE International Conference on Image Processing (ICIP)

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Low Complexity Fast Grid-Based Refining Segmentation in the V-PCC encoder

Cited by 7 publications

References 3 publications

Improved Patch Packing and Refining Segmentation for the V-PCC Standard

Improved Patch Packing and Refining Segmentation for the V-PCC Standard

Simple Grid-Based Refinement Segmentation Algorithm for MPEG Video-Based Point Cloud Compression

Dynamic Point Cloud Compression Approach Using Hexahedron Segmentation

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