TITLE
ENHANCING DEPTH DATA IN TIME-OF-FLIGHT (TOF) CAMERAS: A COMPREHENSIVE COMPARATIVE STUDY OF FILTERING TECHNIQUES
AUTHOR(S)
Alexandar Lyubenov, Stefan Ivanov
ABSTRACT
Time-of-Flight (ToF) cameras have become critical instruments in applications demanding real-time 3D depth sensing, such as robotics, augmented reality, and industrial inspection. However, the accuracy of ToF cameras, including models such as the CamBoard pico flexx, is frequently compromised by depth inaccuracies arising from various noise sources. To mitigate these issues, this study investigates the performance of five established filtering techniques: the Wiener filter, Non-Local Means (NLM) filter, Gaussian filter, Bilateral filter, and Median filter. These methods were applied to depth data captured by the CamBoard pico flexx. The paper presents experimental results demonstrating the effectiveness of each filter in improving the quality of depth maps. Prior studies are referenced to provide additional context for the filtering methodologies employed in ToF camera systems.
DOI
http://www.doi.org/10.70456/UVQG9649
DOWNLOAD
https://unitechsp.tugab.bg/images/2024/5-AR/s6_p28_v4.pdf
How to cite this article:
Alexandar Lyubenov, Stefan Ivanov, ENHANCING DEPTH DATA IN TIME-OF-FLIGHT (TOF) CAMERAS: A COMPREHENSIVE COMPARATIVE STUDY OF FILTERING TECHNIQUES, UNITECH – SELECTED PAPERS - 2024