VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866909029772558336 |
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| author | Deng, Zexin Yuan, Zhenhui Lu, Tian Li, Gaofeng Huang, Meipeng Zou, Longhao |
| author_facet | Deng, Zexin Yuan, Zhenhui Lu, Tian Li, Gaofeng Huang, Meipeng Zou, Longhao |
| contents | Real-time video streaming is crucial in surgical teleoperation, yet reproducible evaluation under realistic network impairments remains limited. This paper presents VISTA, a benchmark designed to study how impairments along the forward video path affect received video quality, temporal continuity, and human task performance. VISTA employs Linux Traffic Control with NetEm and a Gilbert-Elliott loss model to emulate five network conditions: Hospital LAN, 5G Urban, 4G Rural, LEO Satellite, and GEO Satellite. The benchmark integrates a standardised peg transfer task with synchronized measurements of network quality of service (QoS), objective video quality (PSNR, SSIM, and VMAF), and temporal continuity through freeze rate, while maintaining a stable reverse control channel. Across 375 experimental trials, network degradation substantially reduced teleoperation performance: success rate decreased from 97% in Hospital LAN to 79% in 5G Urban, 35% in 4G Rural, 71% in LEO Satellite, and 12% in GEO Satellite, while mean task completion time for successful trials increased from 80 s in Hospital LAN to 117 s in 5G Urban, 211 s in 4G Rural, 152 s in LEO Satellite, and 255 s in GEO Satellite. These findings show that network impairments have a direct impact on task completion and success in surgical teleoperation, and provide a reproducible basis for evaluating teleoperation video under realistic network constraints. Source code available at https://github.com/Dzxx623/VISTA. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_08886 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation Deng, Zexin Yuan, Zhenhui Lu, Tian Li, Gaofeng Huang, Meipeng Zou, Longhao Image and Video Processing Robotics Real-time video streaming is crucial in surgical teleoperation, yet reproducible evaluation under realistic network impairments remains limited. This paper presents VISTA, a benchmark designed to study how impairments along the forward video path affect received video quality, temporal continuity, and human task performance. VISTA employs Linux Traffic Control with NetEm and a Gilbert-Elliott loss model to emulate five network conditions: Hospital LAN, 5G Urban, 4G Rural, LEO Satellite, and GEO Satellite. The benchmark integrates a standardised peg transfer task with synchronized measurements of network quality of service (QoS), objective video quality (PSNR, SSIM, and VMAF), and temporal continuity through freeze rate, while maintaining a stable reverse control channel. Across 375 experimental trials, network degradation substantially reduced teleoperation performance: success rate decreased from 97% in Hospital LAN to 79% in 5G Urban, 35% in 4G Rural, 71% in LEO Satellite, and 12% in GEO Satellite, while mean task completion time for successful trials increased from 80 s in Hospital LAN to 117 s in 5G Urban, 211 s in 4G Rural, 152 s in LEO Satellite, and 255 s in GEO Satellite. These findings show that network impairments have a direct impact on task completion and success in surgical teleoperation, and provide a reproducible basis for evaluating teleoperation video under realistic network constraints. Source code available at https://github.com/Dzxx623/VISTA. |
| title | VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation |
| topic | Image and Video Processing Robotics |
| url | https://arxiv.org/abs/2605.08886 |