Abstract
Knowledge about the interior and exterior camera orientation parameters is required to establish the relationship between 2D image content and 3D object data. Camera calibration is used to determine the interior orientation parameters, which are valid as long as the camera remains stable. However, information about the temporal stability of low-cost cameras due to the physical impact of temperature changes, such as those in smartphones, is still missing. This study investigates on the one hand the influence of heat dissipating smartphone components at the geometric integrity of implemented cameras and on the other hand the impact of ambient temperature changes at the geometry of uncoupled low-cost cameras considering a Raspberry Pi camera module that is exposed to controlled thermal radiation changes. If these impacts are neglected, transferring image measurements into object space will lead to wrong measurements due to high correlations between temperature and camera’s geometric stability. Monte-Carlo simulation is used to simulate temperature-related variations of the interior orientation parameters to assess the extent of potential errors in the 3D data ranging from a few millimetres up to five centimetres on a target in X- and Y-direction. The target is positioned at a distance of 10 m to the camera and the Z-axis is aligned with camera’s depth direction.
Highlights
Smartphones have become indispensable in modern human life as they are not just purely communication tools
To restore the collinearity between the 2D image and the related 3D object scene, i.e., to determine the linear relationships of 2D image points and 3D object points that lie on image rays with a shared origin called projection centre, knowledge about the interior orientation parameters (IOP) is required, which can be determined via photogrammetric camera calibration, e.g., [9,10,11]
Monte-Carlo simulation was applied for each investigated camera as described in Section 3.2, i.e., 50.000 sets of modified IOP are simulated that can result from temperature change
Summary
Smartphones have become indispensable in modern human life as they are not just purely communication tools They are qualified for citizen science applying photogrammetry due to built-in cameras enabling the acquisition and processing of geolocated image data directly on the device. The global increase of climate-related natural hazards [1] demands new technologies to support their observation, detection and forecasting to improve early-warning systems. Current devices comprise high storage capacity, large processing power, a wide range of built-in sensors and high-resolution cameras. They are already a centrepiece in several early warning systems that are supported by volunteered geographic information with user-generated content [2,3]. To restore the collinearity between the 2D image and the related 3D object scene, i.e., to determine the linear relationships of 2D image points and 3D object points that lie on image rays with a shared origin called projection centre, knowledge about the interior orientation parameters (IOP) is required, which can be determined via photogrammetric camera calibration, e.g., [9,10,11]
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