A robust and accurate camera pose determination method based on geometric optimization search using Internet of Things

Qi Wang, Zhangyan Zhao, Enshun Lu, Yang Liu and Licheng Liu

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 6, 1550147719857581

Abstract: We propose a robust and accurate camera pose determination method based on geometric optimization search using the Internet of Things (IoT). The central idea is to (1) obtain image information through Internet of Things technology, (2) obtain the first pose by minimizing the error function, and (3) use the geometric relationship and constraint condition to obtain the appropriate attitude angles as a new initial value for the next iteration calculation. The features of this method are as follows. First, this method can deal with a large amount of uncertain data, such as in the case of any shooting angle, in the case of any reference point, and in the case of a small number of feature points. Finally, because of using Internet of Things technology, our method can quickly complete data processing and transmission. Compared to state-of-the-art methods, the experimental results show that our approach performs well on both synthetic and real data and can be used to provide accurate and stable data for subsequent applications.

Keywords: Camera pose determination; Internet of Things; uncertain data; pose ambiguity; arbitrary initial value (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:6:p:1550147719857581

DOI: 10.1177/1550147719857581

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