Evidence map›Paper›PMID 35898082›Full record

ArticleSensors (Basel, Switzerland)2022

An Effective Camera-to-Lidar Spatiotemporal Calibration Based on a Simple Calibration Target.

Lazaros Grammatikopoulos, Anastasios Papanagnou, Antonios Venianakis, Ilias Kalisperakis, Christos Stentoumis

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
6.4field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 21 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Lazaros Grammatikopoulosup2metric P.C., Engineering-Research-Software Development, Michail Mela 21, 11521 Athens, Greece.
Anastasios Papanagnouup2metric P.C., Engineering-Research-Software Development, Michail Mela 21, 11521 Athens, Greece.ORCID 0000-0002-8991-7629
Antonios Venianakisup2metric P.C., Engineering-Research-Software Development, Michail Mela 21, 11521 Athens, Greece.
Ilias Kalisperakisup2metric P.C., Engineering-Research-Software Development, Michail Mela 21, 11521 Athens, Greece.
Christos Stentoumisup2metric P.C., Engineering-Research-Software Development, Michail Mela 21, 11521 Athens, Greece.ORCID 0000-0001-9972-1761
University of West Attica · GR

Funding

European Commission 825079-RIA
6 · The paper itself

Abstract

In this contribution, we present a simple and intuitive approach for estimating the exterior (geometrical) calibration of a Lidar instrument with respect to a camera as well as their synchronization shifting (temporal calibration) during data acquisition. For the geometrical calibration, the 3D rigid transformation of the camera system was estimated with respect to the Lidar frame on the basis of the establishment of 2D to 3D point correspondences. The 2D points were automatically extracted on images by exploiting an AprilTag fiducial marker, while the detection of the corresponding Lidar points was carried out by estimating the center of a custom-made retroreflective target. Both AprilTag and Lidar reflective targets were attached to a planar board (calibration object) following an easy-to-implement set-up, which yielded high accuracy in the determination of the center of the calibration target. After the geometrical calibration procedure, the temporal calibration was carried out by matching the position of the AprilTag to the corresponding Lidar target (after being projected onto the image frame), during the recording of a steadily moving calibration target. Our calibration framework was given as an open-source software implemented in the ROS platform. We have applied our method to the calibration of a four-camera mobile mapping system (MMS) with respect to an integrated Velodyne Lidar sensor and evaluated it against a state-of-the-art chessboard-based method. Although our method was a single-camera-to-Lidar calibration approach, the consecutive calibration of all four cameras with respect to the Lidar sensor yielded highly accurate results, which were exploited in a multi-camera texturing scheme of city point clouds.

Indexed as

calibration targetcameraextrinsic calibrationLidartemporal calibration

Identifiers

PMID35898082
PMCPMC9329985
OpenAlexW4288069019

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.