Time-of-flight (ToF) cameras can acquire the distance between the sensor and objects with high frame rates, offering bright prospects for ToF cameras in many applications. Low-resolution and depth errors limit the accuracy of ToF cameras, however. In this paper, we present a flexible accuracy improvement method for depth compensation and feature points position correction of ToF cameras. First, a distance-error model of each pixel in the depth image is established to model sinusoidal waves of ToF cameras and compensate for the measured depth data. Second, a more accurate feature point position is estimated with the aid of a high-resolution camera. Experiments evaluate the proposed method, and the result shows the root mean square error is reduced from 4.38 mm to 3.57 mm.
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http://dx.doi.org/10.1364/AO.405703 | DOI Listing |
Sensors (Basel)
December 2024
Department of Electrical Engineering and Information Technology, University of Applied Sciences Mittelhessen, 35390 Giessen, Germany.
Because of their resilience, Time-of-Flight (ToF) cameras are now essential components in scientific and industrial settings. This paper outlines the essential factors for modeling 3D ToF cameras, with specific emphasis on analyzing the phenomenon known as "wiggling". Through our investigation, we demonstrate that wiggling not only causes systematic errors in distance measurements, but also introduces periodic fluctuations in statistical measurement uncertainty, which compounds the dependence on the signal-to-noise ratio (SNR).
View Article and Find Full Text PDFMed Phys
December 2024
Department of Physics, Lakehead University, Thunder Bay, Ontario, Canada.
Background: This study investigates a multi-angle acquisition method aimed at improving image quality in organ-targeted PET detectors with planar detector heads. Organ-targeted PET technologies have emerged to address limitations of conventional whole-body PET/CT systems, such as restricted axial field-of-view (AFOV), limited spatial resolution, and high radiation exposure associated with PET procedures. The AFOV in organ-targeted PET can be adjusted to the organ of interest, minimizing unwanted signals from other parts of the body, thus improving signal collection efficiency and reducing the dose of administered radiotracer.
View Article and Find Full Text PDFSensors (Basel)
October 2024
Department of Agriculture Technology, Faculty of Agriculture, University Putra Malaysia, Serdang 43400, Selangor, Malaysia.
The challenges and drawbacks of manual weeding and herbicide usage, such as inefficiency, high costs, time-consuming tasks, and environmental pollution, have led to a shift in the agricultural industry toward digital agriculture. The utilization of advanced robotic technologies in the process of weeding serves as prominent and symbolic proof of innovations under the umbrella of digital agriculture. Typically, robotic weeding consists of three primary phases: sensing, thinking, and acting.
View Article and Find Full Text PDFJ Imaging
October 2024
Institute for Photonic Systems Hochschule Ravensburg-Weingarten, University of Applied Sciences, Doggenriedstraße, 88250 Weingarten, Germany.
Time-of-Flight (ToF) cameras are subject to high levels of noise and errors due to Multi-Path-Interference (MPI). To correct these errors, algorithms and neuronal networks require training data. However, the limited availability of real data has led to the use of physically simulated data, which often involves simplifications and computational constraints.
View Article and Find Full Text PDFWe introduce a new, to our knowledge, method to measure the arrival time of photons with a sub-nanosecond precision using two conventional cameras. The method exploits the finite rise/fall time of the electro-optical global shutter implemented in modern complementary metal-oxide semiconductor (CMOS) cameras. By mapping the arrival time to the normalized brightness, the time of flight (ToF) can be determined with a precision better than 0.
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