Identification of Location and Camera Parameters for Public Live Streaming Web Cameras

Public live streaming web cameras are quite common now and widely used by drivers for qualitative analysis of traffic conditions. At the same time, they can be a valuable source of quantitative information on transport flows and speed for the development of urban traffic models. However, to obtain r...

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Main Authors: Aleksander Zatserkovnyy, Evgeni Nurminski
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/10/19/3601
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author Aleksander Zatserkovnyy
Evgeni Nurminski
author_facet Aleksander Zatserkovnyy
Evgeni Nurminski
author_sort Aleksander Zatserkovnyy
collection DOAJ
description Public live streaming web cameras are quite common now and widely used by drivers for qualitative analysis of traffic conditions. At the same time, they can be a valuable source of quantitative information on transport flows and speed for the development of urban traffic models. However, to obtain reliable data from raw video streams, it is necessary to preprocess them, considering the camera location and parameters without direct access to the camera. Here we suggest a procedure for estimating camera parameters, which allows us to determine pixel coordinates for a point cloud in the camera’s view field and transform them into metric data. They are used with advanced moving object detection and tracking for measurements.
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spelling doaj.art-879b5890e79c4c0082ca40101c6ada7e2023-11-23T21:04:17ZengMDPI AGMathematics2227-73902022-10-011019360110.3390/math10193601Identification of Location and Camera Parameters for Public Live Streaming Web CamerasAleksander Zatserkovnyy0Evgeni Nurminski1Pacific Oceanological Institute of Far Eastern Branch of RAS, 690041 Vladivostok, RussiaCenter for Research and Education in Mathematics, Institute of Mathematics and Computer Technologies, Far Eastern Federal University, 690922 Vladivostok, RussiaPublic live streaming web cameras are quite common now and widely used by drivers for qualitative analysis of traffic conditions. At the same time, they can be a valuable source of quantitative information on transport flows and speed for the development of urban traffic models. However, to obtain reliable data from raw video streams, it is necessary to preprocess them, considering the camera location and parameters without direct access to the camera. Here we suggest a procedure for estimating camera parameters, which allows us to determine pixel coordinates for a point cloud in the camera’s view field and transform them into metric data. They are used with advanced moving object detection and tracking for measurements.https://www.mdpi.com/2227-7390/10/19/3601depth mapradial distortionperspective distortioncamera calibrationtransport traffic statistics
spellingShingle Aleksander Zatserkovnyy
Evgeni Nurminski
Identification of Location and Camera Parameters for Public Live Streaming Web Cameras
Mathematics
depth map
radial distortion
perspective distortion
camera calibration
transport traffic statistics
title Identification of Location and Camera Parameters for Public Live Streaming Web Cameras
title_full Identification of Location and Camera Parameters for Public Live Streaming Web Cameras
title_fullStr Identification of Location and Camera Parameters for Public Live Streaming Web Cameras
title_full_unstemmed Identification of Location and Camera Parameters for Public Live Streaming Web Cameras
title_short Identification of Location and Camera Parameters for Public Live Streaming Web Cameras
title_sort identification of location and camera parameters for public live streaming web cameras
topic depth map
radial distortion
perspective distortion
camera calibration
transport traffic statistics
url https://www.mdpi.com/2227-7390/10/19/3601
work_keys_str_mv AT aleksanderzatserkovnyy identificationoflocationandcameraparametersforpubliclivestreamingwebcameras
AT evgeninurminski identificationoflocationandcameraparametersforpubliclivestreamingwebcameras