Revisiting Rolling Shutter Bundle Adjustment: Toward Accurate and Fast Solution

• URL: http://arxiv.org/abs/2209.08503v3
• Date: Tue, 18 Apr 2023 14:16:24 GMT
• Title: Revisiting Rolling Shutter Bundle Adjustment: Toward Accurate and Fast Solution
• Authors: Bangyan Liao, Delin Qu, Yifei Xue, Huiqing Zhang, Yizhen Lao
• Abstract summary: We propose a robust and fast bundle adjustment solution that estimates the 6-DoF pose of the camera and the geometry of the environment based on measurements from a rolling shutter (RS) camera. This tackles the challenges in the existing works, namely relying on additional sensors, high frame rate video as input, restrictive assumptions on camera motion, readout direction, and poor efficiency.
• Score: 6.317266060165099
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a robust and fast bundle adjustment solution that estimates the 6-DoF pose of the camera and the geometry of the environment based on measurements from a rolling shutter (RS) camera. This tackles the challenges in the existing works, namely relying on additional sensors, high frame rate video as input, restrictive assumptions on camera motion, readout direction, and poor efficiency. To this end, we first investigate the influence of normalization to the image point on RSBA performance and show its better approximation in modelling the real 6-DoF camera motion. Then we present a novel analytical model for the visual residual covariance, which can be used to standardize the reprojection error during the optimization, consequently improving the overall accuracy. More importantly, the combination of normalization and covariance standardization weighting in RSBA (NW-RSBA) can avoid common planar degeneracy without needing to constrain the filming manner. Besides, we propose an acceleration strategy for NW-RSBA based on the sparsity of its Jacobian matrix and Schur complement. The extensive synthetic and real data experiments verify the effectiveness and efficiency of the proposed solution over the state-of-the-art works. We also demonstrate the proposed method can be easily implemented and plug-in famous GSSfM and GSSLAM systems as completed RSSfM and RSSLAM solutions.

Related papers

• ESVO2: Direct Visual-Inertial Odometry with Stereo Event Cameras [33.81592783496106]
  Event-based visual odometry aims at solving tracking and mapping sub-problems in parallel. We build an event-based stereo visual-inertial odometry system on top of our previous direct pipeline Event-based Stereo Visual Odometry.
  arXiv  Detail & Related papers  (2024-10-12T05:35:27Z)
• SLAIM: Robust Dense Neural SLAM for Online Tracking and Mapping [15.63276368052395]
  We propose a novel coarse-to-fine tracking model tailored for Neural Radiance Field SLAM (NeRF-SLAM) Existing NeRF-SLAM systems consistently exhibit inferior tracking performance compared to traditional SLAM algorithms. We implement both local and global bundle-adjustment to produce a robust (coarse-to-fine) and accurate (KL regularizer) SLAM solution.
  arXiv  Detail & Related papers  (2024-04-17T14:23:28Z)
• Robust Gaussian Splatting [22.400956166196842]
  We address common error sources for 3D Gaussian Splatting (3DGS) including blur, imperfect camera poses, and color inconsistencies. We propose mechanisms for defocus blur compensation and for addressing color in-consistencies caused by ambient light, shadows, or due to camera-related factors like varying white balancing settings.
  arXiv  Detail & Related papers  (2024-04-05T16:42:16Z)
• Toward Efficient Visual Gyroscopes: Spherical Moments, Harmonics Filtering, and Masking Techniques for Spherical Camera Applications [83.8743080143778]
  A visual gyroscope estimates camera rotation through images. The integration of omnidirectional cameras, offering a larger field of view compared to traditional RGB cameras, has proven to yield more accurate and robust results. Here, we address these challenges by introducing a novel visual gyroscope, which combines an Efficient Multi-Mask-Filter Rotation Estor and a Learning based optimization.
  arXiv  Detail & Related papers  (2024-04-02T13:19:06Z)
• Pointless Global Bundle Adjustment With Relative Motions Hessians [0.0]
  We propose a new bundle adjustment objective which does not rely on image features' reprojection errors. Our method averages over relative motions while implicitly incorporating the contribution of the structure in the adjustment. We argue that this approach is an upgraded version of the motion averaging approach and demonstrate its effectiveness on both photogrammetric datasets and computer vision benchmarks.
  arXiv  Detail & Related papers  (2023-04-11T10:20:32Z)
• An Adaptive Method for Camera Attribution under Complex Radial Distortion Corrections [77.34726150561087]
  In-camera or out-camera software/firmware alters the supporting grid of the image so as to hamper PRNU-based camera attribution. Existing solutions to deal with this problem try to invert/estimate the correction using radial transformations parameterized with few variables in order to restrain the computational load. We propose an adaptive algorithm that by dividing the image into concentric annuli is able to deal with sophisticated corrections like those applied out-camera by third party software like Adobe Lightroom, Photoshop, Gimp and PT-Lens.
  arXiv  Detail & Related papers  (2023-02-28T08:44:00Z)
• Learning Adaptive Warping for Real-World Rolling Shutter Correction [52.45689075940234]
  This paper proposes the first real-world rolling shutter (RS) correction dataset, BS-RSC, and a corresponding model to correct the RS frames in a distorted video. Mobile devices in the consumer market with CMOS-based sensors for video capture often result in rolling shutter effects when relative movements occur during the video acquisition process.
  arXiv  Detail & Related papers  (2022-04-29T05:13:50Z)
• Neural Global Shutter: Learn to Restore Video from a Rolling Shutter Camera with Global Reset Feature [89.57742172078454]
  Rolling shutter (RS) image sensors suffer from geometric distortion when the camera and object undergo motion during capture. In this paper, we investigate using rolling shutter with a global reset feature (RSGR) to restore clean global shutter (GS) videos. This feature enables us to turn the rectification problem into a deblur-like one, getting rid of inaccurate and costly explicit motion estimation.
  arXiv  Detail & Related papers  (2022-04-03T02:49:28Z)
• Universal and Flexible Optical Aberration Correction Using Deep-Prior Based Deconvolution [51.274657266928315]
  We propose a PSF aware plug-and-play deep network, which takes the aberrant image and PSF map as input and produces the latent high quality version via incorporating lens-specific deep priors. Specifically, we pre-train a base model from a set of diverse lenses and then adapt it to a given lens by quickly refining the parameters.
  arXiv  Detail & Related papers  (2021-04-07T12:00:38Z)
• Pushing the Envelope of Rotation Averaging for Visual SLAM [69.7375052440794]
  We propose a novel optimization backbone for visual SLAM systems. We leverage averaging to improve the accuracy, efficiency and robustness of conventional monocular SLAM systems. Our approach can exhibit up to 10x faster with comparable accuracy against the state-art on public benchmarks.
  arXiv  Detail & Related papers  (2020-11-02T18:02:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.