Next Article in Journal
Functionally Graded Plate Fracture Analysis Using the Field Boundary Element Method
Next Article in Special Issue
Parameter Optimization of dsRNA Splicing Evolutionary Algorithm Based Fixed-Time Obstacle-Avoidance Trajectory Planning for Space Robot
Previous Article in Journal
FTIR Spectroscopy for Identification and Intra-Species Characterization of Serpula lacrymans

Equal Baseline Camera Array—Calibration, Testbed and Applications

Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, ul. G. Narutowicza 11/12, 80-233 Gdansk, Poland
Center for Vision, Automation and Control, AIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria
Author to whom correspondence should be addressed.
Academic Editors: Jarosław Panasiuk, Wojciech Kaczmarek and Albert Smalcerz
Appl. Sci. 2021, 11(18), 8464;
Received: 10 August 2021 / Revised: 2 September 2021 / Accepted: 8 September 2021 / Published: 12 September 2021
(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)
This paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative to other 3D imaging equipment such as Structured-light 3D scanners or Light Detection and Ranging (LIDAR). The considered kinds of arrays are called Equal Baseline Camera Array (EBCA). This paper presents a novel approach to calibrating the array based on the use of self-calibration methods. This paper also introduces a testbed which makes it possible to develop new algorithms for obtaining 3D data from images taken by the array. The testbed was released under open-source. Moreover, this paper shows new results of using these arrays with different stereo matching algorithms including an algorithm based on a convolutional neural network and deep learning technology. View Full-Text
Keywords: stereo camera; camera array; depth sensor; disparity map; depth map; 3D vision; camera array calibration stereo camera; camera array; depth sensor; disparity map; depth map; 3D vision; camera array calibration
Show Figures

Figure 1

MDPI and ACS Style

Kaczmarek, A.L.; Blaschitz, B. Equal Baseline Camera Array—Calibration, Testbed and Applications. Appl. Sci. 2021, 11, 8464.

AMA Style

Kaczmarek AL, Blaschitz B. Equal Baseline Camera Array—Calibration, Testbed and Applications. Applied Sciences. 2021; 11(18):8464.

Chicago/Turabian Style

Kaczmarek, Adam L., and Bernhard Blaschitz. 2021. "Equal Baseline Camera Array—Calibration, Testbed and Applications" Applied Sciences 11, no. 18: 8464.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop