Fast automatic camera network calibration through human mesh recovery

Camera calibration is a necessary preliminary step in computer vision for the estimation of the position of objects in the 3D world. Despite the intrinsic camera parameters can be easily computed offline, extrinsic parameters need to be computed each time a camera changes its position, thus not allo...

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Vydáno v:Journal of real-time image processing Ročník 17; číslo 6; s. 1757 - 1768
Hlavní autoři: Garau, Nicola, De Natale, Francesco G. B., Conci, Nicola
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2020
Springer Nature B.V
Témata:
Accuracy
Calibration
Cameras
Color imagery
Computation
Computer Graphics
Computer Science
Computer vision
Deep learning
Image Processing and Computer Vision
Multimedia Information Systems
Parameters
Pattern Recognition
Recovery
Sensors
Signal,Image and Speech Processing
Special Issue Paper
Surveillance
Camera calibration
Human mesh recovery
Pose estimation
3D matching
ISSN:1861-8200, 1861-8219
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Shrnutí:Camera calibration is a necessary preliminary step in computer vision for the estimation of the position of objects in the 3D world. Despite the intrinsic camera parameters can be easily computed offline, extrinsic parameters need to be computed each time a camera changes its position, thus not allowing for fast and dynamic network re-configuration. In this paper we present an unsupervised and automatic framework for the estimation of the extrinsic parameters of a camera network, which leverages on optimised 3D human mesh recovery from a single image, and which does not require the use of additional markers. We show how it is possible to retrieve the real-world position of the cameras in the network together with the floor plane, exploiting regular RGB images and with a weak prior knowledge of the internal parameters. Our framework can also work with a single camera and in real-time, allowing the user to add, re-position, or remove cameras from the network in a dynamic fashion.
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ISSN:1861-8200
1861-8219
DOI:10.1007/s11554-020-01002-w