Citation Link: https://doi.org/10.1109/JSEN.2023.3273165
Performance Evaluation of State-of-the-Art High-Resolution Time-of-Flight Cameras
Publication Type
Article
Subjects
Time of flight
Computer science
Artificial intelligence
Computer vision
Pixel
Image resolution
Waveform
Enhanced Data Rates for GSM Evolution
Noise (video)
Point cloud
Lidar
Power (physics)
Optics
Image (mathematics)
Physics
Radar
Telecommunications
Date Issued
2023
Abstract
It has been about 20 years since the disruptive appearance of the first Time-of-Flight (ToF) cameras. Since then, ToF imaging has progressively evolved. Nowadays, ToF sensors have broken the barrier of the 1 MPix resolution and a significant number of high-resolution ToF cameras has appeared in the market. In order to provide a better understanding of their performance and applications, we experimentally evaluate three state-of-the-art high-resolution ToF cameras such as Azure Kinect, Helios2, and S100D, together with the solid-state LiDAR L515. We perform various experiments to examine some key parameters, such as warm-up times, accuracy, precision, lateral and axial resolutions, edge noise, unsteady scenes, and modulated waveform and optical power. Our evaluation draws various conclusions: S100D shows fluctuations within 1 mm after being powered up while the others require warm-up times. Azure Kinect, Helios2, and L515 can achieve precision within 2 mm in a measuring range of 0.5 m to 3 m. Helios2 and S100D are more severely affected by dynamic scenes. Finally, the point clouds generated for a white panel at a distance of 1.5 m show that flying pixels are present in all cameras, being this problem less acute for the L515.
Owning collection