Parametric evaluation of observed objects from images based on perspective geometry methods and convolutional neural networks

M. L. Kazaryan; A. A. Richter; A. B. Murynin; O. G. Gvozdev; V. A. Kozub; D. Yu. Pukhovsky; A. Zelensky; E. Semenishchev

doi:10.1117/12.2646261

4 January 2023 Parametric evaluation of observed objects from images based on perspective geometry methods and convolutional neural networks

M. L. Kazaryan, A. A. Richter, A. B. Murynin, O. G. Gvozdev, V. A. Kozub, D. Yu. Pukhovsky, A. Zelensky, E. Semenishchev

Author Affiliations +

Proceedings Volume 12317, Optoelectronic Imaging and Multimedia Technology IX; 123171E (2023) https://doi.org/10.1117/12.2646261
Event: SPIE/COS Photonics Asia, 2022, Online Only

Conference Poster

Abstract

We proposed an approach for estimating the shape and geometric parameters of the observed objects from a perspective image based on typed elements, perspective geometry methods and convolutional neural networks. The proposed method uses the assumption that the object under study is rigid. A method is proposed for restoring a 3-D model of an observed object from one perspective image using reference objects and typed elements. Semantic segmentation of typed elements allows to set the photometric parameters of the coordinate system attached to the points on the image. According to the calculated photometric parameters and segmentation of the observed object in the image, its parameters and a 3-D model are estimated. The developed method is applicable for calculating 3-D models from a single perspective image in the vicinity of a road (both road and railway) infrastructure, where there are a large number of typed elements.

Citation Download Citation

M. L. Kazaryan, A. A. Richter, A. B. Murynin, O. G. Gvozdev, V. A. Kozub, D. Yu. Pukhovsky, A. Zelensky, and E. Semenishchev "Parametric evaluation of observed objects from images based on perspective geometry methods and convolutional neural networks", Proc. SPIE 12317, Optoelectronic Imaging and Multimedia Technology IX, 123171E (4 January 2023); https://doi.org/10.1117/12.2646261

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available