1,119 research outputs found
CoBe -- Coded Beacons for Localization, Object Tracking, and SLAM Augmentation
This paper presents a novel beacon light coding protocol, which enables fast
and accurate identification of the beacons in an image. The protocol is
provably robust to a predefined set of detection and decoding errors, and does
not require any synchronization between the beacons themselves and the optical
sensor. A detailed guide is then given for developing an optical tracking and
localization system, which is based on the suggested protocol and readily
available hardware. Such a system operates either as a standalone system for
recovering the six degrees of freedom of fast moving objects, or integrated
with existing SLAM pipelines providing them with error-free and easily
identifiable landmarks. Based on this guide, we implemented a low-cost
positional tracking system which can run in real-time on an IoT board. We
evaluate our system's accuracy and compare it to other popular methods which
utilize the same optical hardware, in experiments where the ground truth is
known. A companion video containing multiple real-world experiments
demonstrates the accuracy, speed, and applicability of the proposed system in a
wide range of environments and real-world tasks. Open source code is provided
to encourage further development of low-cost localization systems integrating
the suggested technology at its navigation core
Revisiting Rolling Shutter Bundle Adjustment: Toward Accurate and Fast Solution
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
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields
Neural Radiance Fields (NeRF) has received much attention recently due to its
impressive capability to represent 3D scene and synthesize novel view images.
Existing works usually assume that the input images are captured by a global
shutter camera. Thus, rolling shutter (RS) images cannot be trivially applied
to an off-the-shelf NeRF algorithm for novel view synthesis. Rolling shutter
effect would also affect the accuracy of the camera pose estimation (e.g. via
COLMAP), which further prevents the success of NeRF algorithm with RS images.
In this paper, we propose Unrolling Shutter Bundle Adjusted Neural Radiance
Fields (USB-NeRF). USB-NeRF is able to correct rolling shutter distortions and
recover accurate camera motion trajectory simultaneously under the framework of
NeRF, by modeling the physical image formation process of a RS camera.
Experimental results demonstrate that USB-NeRF achieves better performance
compared to prior works, in terms of RS effect removal, novel view image
synthesis as well as camera motion estimation. Furthermore, our algorithm can
also be used to recover high-fidelity high frame-rate global shutter video from
a sequence of RS images
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