Buy article PDF
The purchased file will be sent to you
via email after the payment is completed.
US$ 35
|
Computers and Concrete Volume 33, Number 5, May 2024 (Special Issue) pages 535-544 DOI: https://doi.org/10.12989/cac.2024.33.5.535 |
|
|
|
Markerless camera pose estimation framework utilizing construction material with standardized specification |
||
Harim Kim, Heejae Ahn, Sebeen Yoon, Taehoon Kim, Thomas H.-K. Kang, Young K. Ju, Minju Kim and Hunhee Cho
|
||
| Abstract | ||
| In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-npoint (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure. | ||
| Key Words | ||
| computer vision; image processing; keypoint detection; markerless pose estimation | ||
| Address | ||
| Harim Kim, Heejae Ahn, Young K. Ju and Hunhee Cho: Department of Civil, Environmental and Architectural Engineering, Korea University, Seongbuk-Gu, Seoul 02841, Republic of Korea Sebeen Yoon and Taehoon Kim: Department of Architectural Engineering, Seoul National University of Science and Technology, 232, Gongneung-ro, Nowon-gu, Seoul, 01811, Republic of Korea Thomas H.-K. Kang: Department of Architecture and Architectural Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea Minju Kim: Department of Construction Management, University of Washington, Seattle, WA 98105, United States of America | ||