Evaluation of low-cost depth cameras for agricultural applications

Authors

Isabella C.F.S. Condotta, “Luiz de Queiroz” College of Agriculture & University of Nebraska-Lincoln & University of Illinois at Urbana Champaign
T. M. Brown-Brandl, University of Nebraska-Lincoln & USDA, Agricultural Research ServiceFollow
Santosh Pitla, University of Nebraska-LincolnFollow
John P. Stinn, Iowa Select Farms
Késia O. Silva-Miranda, “Luiz de Queiroz” College of Agriculture

Date of this Version

2020

Citation

Computers and Electronics in Agriculture 173 (2020) 105394

https://doi.org/10.1016/j.compag.2020.105394

Comments

U.S. government works are not subject to copyright.

Abstract

Low-cost depth-cameras have been used in many agricultural applications with reported advantages of low cost, reliability and speed of measurement. However, some problems were also reported and seem to be technology- related, so understanding the limitations of each type of depth camera technology could provide a basis for technology selection and the development of research involving its use. The cameras use one or a combination of two of the three available technologies: structured light, time-of-flight (ToF), and stereoscopy. The objectives were to evaluate these different technologies for depth sensing, including measuring accuracy and repeatability of distance data and measurements at different positions within the image, and cameras usefulness in indoor and outdoor settings. Then, cameras were tested in a swine facility and in a corn field. Five different cameras were used: (1) Microsoft Kinect v.1, (2) Microsoft Kinect v.2, (3) Intel® RealSenseTM Depth Camera D435, (4) ZED Stereo Camera (StereoLabs), and (5) CamBoard Pico Flexx (PMD Technologies). Results indicate that there were significant camera to camera differences for ZED Stereo Camera and Kinect v.1 camera (p < 0.05). All cameras showed an increase in the standard deviation as the distance between camera and object increased; however, the Intel RealSense camera had a larger increase. Time-of-flight cameras had the smallest error between different sizes of objects. Time-of-flight cameras had non-readable zones on the corners of the images. The results indicate that the ToF technology is the best to be used for indoor applications and stereoscopy is the best technology for outdoor applications.