Budget-aware Correspondence-driven View Selection for Real-time 3D Perception of Mobile Robots
Budget-aware Correspondence-driven View Selection for Real-time 3D Perception of Mobile Robots
This research introduces BCVS, a pose-free view selection algorithm that enables real-time 3D perception on mobile robots by iteratively selecting novel frames within a user-specified budget. The method suppresses near-duplicates to minimize reconstruction loss and reduces image redundancy by up to 16% in field trials with aerial and marine robotics data while sustaining robust structure-from-motion registration, outperforming CPU-friendly baselines at tight budgets.
The authors present a correspondence-driven view selection algorithm (BCVS) that achieves over 22 FPS on CPU without requiring camera pose estimation, reducing image redundancy by up to 16% in field trials with aerial and marine robotics data while maintaining robust structure-from-motion registration.
Source: arXiv Robotics — research abstracts · Read original article ↗
Loading article text…
What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
FPS on CPU
>22
View original evidence
arXiv:2611.11809v1 Announce Type: new Abstract: 3D visual perception and scene reconstruction are critical for autonomous robots and intelligent transportation, yet real-world deployments often generate long, redundant image sequences that hinder downstream processing. This report investigates BCVS (budget-aware correspondence-driven view sampling), a pose-free view selection algorithm that offers 22+ FPS on a CPU, e
Open source S2
- paper: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
ppresses near-duplicates, producing compact subsets that preserve connectivity and minimize reconstruction loss. Extensive experiments on benchmark show that BCVS outperforms CPU-friendly baselines at tight budgets and remains competitive as budgets scale. Field trials with large aerial and marine robotics data further validate its practicality and scalability: BCVS reduces redundancy up to 16% while sustaining robus
Open source S4
arXiv:2611.11809v1 Announce Type: new Abstract: 3D visual perception and scene reconstruction are critical for autonomous robots and intelligent transportation, yet real-world deployments often generate long, redundant image sequences that hinder downstream processing. This report investigates BCVS (budget-aware correspondence-driven view sampling), a pose-free view selection algorithm that offers 22+ FPS on a CPU, e
Open source S2
Source：arXiv Robotics — research abstracts · arxiv.org