A Method to Compensate for the Errors Caused by Temperature in Structured-Light 3D Cameras

Vila, Oriol; Boada, Imma; Raba, David; Farrés, E.

doi:10.3390/s21062073

Cited by 3 publications

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The first set of experiments utilizes the Middlebury stereo matching dataset. The second set of experiments involves using grayscale and depth images captured by the Orbbec [24,25] Astra S sensor to perform depth restoration in indoor scenes.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Non-Local Means Hole Repair Algorithm Based on Adaptive Block

Zhao,

Li,

Pan

2023

Applied Sciences

View full text Add to dashboard Cite

RGB-D cameras provide depth and color information and are widely used in 3D reconstruction and computer vision. In the majority of existing RGB-D cameras, a considerable portion of depth values is often lost due to severe occlusion or limited camera coverage, thereby adversely impacting the precise localization and three-dimensional reconstruction of objects. In this paper, to address the issue of poor-quality in-depth images captured by RGB-D cameras, a depth image hole repair algorithm based on non-local means is proposed first, leveraging the structural similarities between grayscale and depth images. Second, while considering the cumbersome parameter tuning associated with the non-local means hole repair method for determining the size of structural blocks for depth image hole repair, an intelligent block factor is introduced, which automatically determines the optimal search and repair block sizes for various hole sizes, resulting in the development of an adaptive block-based non-local means algorithm for repairing depth image holes. Furthermore, the proposed algorithm’s performance are evaluated using both the Middlebury stereo matching dataset and a self-constructed RGB-D dataset, with performance assessment being carried out by comparing the algorithm against other methods using five metrics: RMSE, SSIM, PSNR, DE, and ALME. Finally, experimental results unequivocally demonstrate the innovative resolution of the parameter tuning complexity inherent in-depth image hole repair, effectively filling the holes, suppressing noise within depth images, enhancing image quality, and achieving elevated precision and accuracy, as affirmed by the attained results.

show abstract

Section: Experimental Results and Analysismentioning

confidence: 99%

Non-Local Means Hole Repair Algorithm Based on Adaptive Block

Zhao,

Li,

Pan

2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

Application of Generative Adversarial Networks in Gesture Recognition

Zhu

Yang

Chen

et al. 2022

2022 WRC Symposium on Advanced Robotics and Automation (WRC SARA)

View full text Add to dashboard Cite

Point Cloud Measurement of Rubber Tread Dimension Based on RGB-Depth Camera

Huang,

Chen,

Peng

2024

Applied Sciences

View full text Add to dashboard Cite

To achieve an accurate measurement of tread size after fixed-length cutting, this paper proposes a point-cloud-based tread size measurement method. Firstly, a mathematical model of corner points and a reprojection error is established, and the optimal solution of the number of corner points is determined by the non-dominated sorting genetic algorithm II (NSGA-II), which reduces the reprojection error of the RGB-D camera. Secondly, to address the problem of the low accuracy of the traditional pixel metric ratio measurement method, the random sampling consensus point cloud segmentation algorithm (RANSAC) and the oriented bounding box (OBB) collision detection algorithm are introduced to complete the accurate detection of the tread size. By comparing the absolute error and relative error data of several groups of experiments, the accuracy of the detection method in this paper reaches 1 mm, and the measurement deviation is between 0.14% and 2.67%, which is in line with the highest accuracy standard of the national standard. In summary, the RGB-D visual inspection method constructed in this paper has the characteristics of low cost and high inspection accuracy, which is a potential solution to enhance the pickup guidance of tread size measurement.

show abstract

A Method to Compensate for the Errors Caused by Temperature in Structured-Light 3D Cameras

Cited by 3 publications

References 31 publications

Non-Local Means Hole Repair Algorithm Based on Adaptive Block

Non-Local Means Hole Repair Algorithm Based on Adaptive Block

Application of Generative Adversarial Networks in Gesture Recognition

Point Cloud Measurement of Rubber Tread Dimension Based on RGB-Depth Camera

Contact Info

Product

Resources

About