High accuracy smartphone video calibration for human foot surface mapping

Al-Kharaz, Ali A. and Chong, Albert K. (2018) High accuracy smartphone video calibration for human foot surface mapping. In: 2018 3rd IEEE International Conference on Image, Vision and Computing (ICIVC 2018), 27-29 June 2018, Chongqing, China.

Abstract

Although the digital camera is readily available and the price is decreasing, many users still consider it an expensive device that can be dispensed with by using a smart phone camera. However, both the digital camera and the smartphone need to be calibrated to extract three dimensional (3D) space information from (2D) and to obtain accurate results. This study used close range photogrammetry to calibrate two high resolution digital cameras and a Samsung Galaxy smartphone to find whether any one of them give high accuracy 3D coordinates of the retro-reflective targets that were determined using the self-calibration bundle adjustment method in two phases. The first phase is during walking when 3 trials are conducted. The same three cameras are used for each trial. The second phase is during standing when one trial is conducted. Each of the camera types is placed in front of the platform. The results showed that arguably, the Samsung Galaxy S6 camera is most significant than other cameras in term of accuracy. In addition, this study provides information on how to calibrate one board from other board that has already been calibrated.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 16 Apr 2019 05:11
Last Modified: 17 Apr 2019 01:49
Uncontrolled Keywords: calibration; smartphone; human foot; bundle adjustment; scale bar
Fields of Research : 09 Engineering > 0905 Civil Engineering > 090506 Structural Engineering
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1109/ICIVC.2018.8492792
URI: http://eprints.usq.edu.au/id/eprint/35139

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