TY - GEN
T1 - Development of Photogrammetry Application for 3D Surface Reconstruction
AU - Kurniawan, Wendy Cahya
AU - Wibowo, Fauzy Satrio
AU - Lin, Hsien I.
AU - Handayani, Anik Nur
AU - Sendari, Siti
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Photogrammetry has long been used to collect three-dimensional (3D) information about objects or texture data. The 3D reproduction of real-life objects can be highly useful in a variety of fields, such as archeology, medicine, and geology. The advantages of photogrammetry research with lasers reduce costs, time to digitize objects, and have high accuracy and efficiency. This research aims to design an application that processes 2D image input data into 3D. The features contained in this application include data collection, calibration, image rectification, feature detection, and scanned images. The development of this application has succeeded in reconstructing 2D images into 3D images. In the test, the average visible point detection point is 185.4 and the mean re-projection error is 0.7542. The minimum calibration error must be obtained so that the surface reconstruction results are close to the actual shape. In the future, we would extend our work by manipulating robot movement with photogrammetry as input data.
AB - Photogrammetry has long been used to collect three-dimensional (3D) information about objects or texture data. The 3D reproduction of real-life objects can be highly useful in a variety of fields, such as archeology, medicine, and geology. The advantages of photogrammetry research with lasers reduce costs, time to digitize objects, and have high accuracy and efficiency. This research aims to design an application that processes 2D image input data into 3D. The features contained in this application include data collection, calibration, image rectification, feature detection, and scanned images. The development of this application has succeeded in reconstructing 2D images into 3D images. In the test, the average visible point detection point is 185.4 and the mean re-projection error is 0.7542. The minimum calibration error must be obtained so that the surface reconstruction results are close to the actual shape. In the future, we would extend our work by manipulating robot movement with photogrammetry as input data.
KW - 3D image reconstruction
KW - 3D model
KW - Laser scanner
KW - Photogrammetry
UR - http://www.scopus.com/inward/record.url?scp=85123578789&partnerID=8YFLogxK
U2 - 10.1109/ICEEIE52663.2021.9616728
DO - 10.1109/ICEEIE52663.2021.9616728
M3 - Conference contribution
AN - SCOPUS:85123578789
T3 - 7th International Conference on Electrical, Electronics and Information Engineering: Technological Breakthrough for Greater New Life, ICEEIE 2021
BT - 7th International Conference on Electrical, Electronics and Information Engineering
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Electrical, Electronics and Information Engineering, ICEEIE 2021
Y2 - 2 October 2021
ER -