Visual Odometry for Vehicles’ Undercarriage 3D Modelling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332334" target="_blank" >RIV/68407700:21230/19:00332334 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/19:00332334

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-14984-0_9" target="_blank" >https://doi.org/10.1007/978-3-030-14984-0_9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-14984-0_9" target="_blank" >10.1007/978-3-030-14984-0_9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Visual Odometry for Vehicles’ Undercarriage 3D Modelling

Popis výsledku v původním jazyce

This work describes a part of a project developing a vehicles’ undercarriage security scanner based only on cameras. The scanner is used to a security check of a vehicle’s undercarriage and is typically installed at an entrance to a strategic compund. The security scanner reconstruct a 3D model of a vehicle’s undercarriage from a sequence of a multi-camera stereo images. To get a complete model we need to stitch particular parts of the 3D model via transformations between particular vehicle positions in which images are captured. The method for getting these transformations is presented in this paper. The task of computing trajectory from a sequence of camera images is called visual odometry (VO). Usually, the camera is placed on a moving object and tracks its position. In our case, the camera is fixed and viewing a moving vehicle, but the task is the same. In the first part, there is a comparison of feature detectors and their parameters based on experimental data because the images properties of undercarriage are different from ordinary surroundings used by the most of VO methods. Undercarriages do not contain a lot of features, and there are many low-textured surfaces. In the second part, the proposed VO method is described. It is based on the best feature from the first part, which serves to search corresponding points between images. It uses 3D to 2D VO method to compute the transformation between consecutive frames. In this method, 3D points are triangulated from the previous pair of stereo camera images, and they are reprojected to one of the actual images. The method finds the transformation of 3D positions which minimizes reprojection error. The method was developed with respect to requirement of almost real-time computing time and low-texture environment. Finally, this method was evaluated on realistic data acquired with ground truth position.

Název v anglickém jazyce

Visual Odometry for Vehicles’ Undercarriage 3D Modelling

Popis výsledku anglicky

This work describes a part of a project developing a vehicles’ undercarriage security scanner based only on cameras. The scanner is used to a security check of a vehicle’s undercarriage and is typically installed at an entrance to a strategic compund. The security scanner reconstruct a 3D model of a vehicle’s undercarriage from a sequence of a multi-camera stereo images. To get a complete model we need to stitch particular parts of the 3D model via transformations between particular vehicle positions in which images are captured. The method for getting these transformations is presented in this paper. The task of computing trajectory from a sequence of camera images is called visual odometry (VO). Usually, the camera is placed on a moving object and tracks its position. In our case, the camera is fixed and viewing a moving vehicle, but the task is the same. In the first part, there is a comparison of feature detectors and their parameters based on experimental data because the images properties of undercarriage are different from ordinary surroundings used by the most of VO methods. Undercarriages do not contain a lot of features, and there are many low-textured surfaces. In the second part, the proposed VO method is described. It is based on the best feature from the first part, which serves to search corresponding points between images. It uses 3D to 2D VO method to compute the transformation between consecutive frames. In this method, 3D points are triangulated from the previous pair of stereo camera images, and they are reprojected to one of the actual images. The method finds the transformation of 3D positions which minimizes reprojection error. The method was developed with respect to requirement of almost real-time computing time and low-texture environment. Finally, this method was evaluated on realistic data acquired with ground truth position.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/VI20172020080" target="_blank" >VI20172020080: Kassandra - mnohokamerový bezpečnostní skener podvozků vozidel</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Modelling and Simulation for Autonomous Systems (MESAS 2018)

ISBN

978-3-030-14983-3

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

10

Strana od-do

111-120

Název nakladatele

Springer International Publishing AG

Místo vydání

Cham

Místo konání akce

Praha

Datum konání akce

17. 10. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000554861000009