Dynamic feature removal method based on relative geometry

Shaojie Meng; Miaohua Huang; Yang Hou; Yanyong Ren

doi:10.1117/12.2671163

28 April 2023 Dynamic feature removal method based on relative geometry

Shaojie Meng, Miaohua Huang, Yang Hou, Yanyong Ren

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126103M (2023) https://doi.org/10.1117/12.2671163
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Simultaneous Localization and Mapping (SLAM) research has become a hot spot in computer vision field. Static worlds are assumed in most existing SLAM systems. When traditional systems work in dynamic environment, the results of visual odometer will be affected by dynamic objects, resulting in low matching accuracy and poor performance. Aiming at the poor performance of traditional algorithms in dynamic environment, this paper proposes a new feature point extraction algorithm based on local feature matching relative geometry structure, which can efficiently extract robust features from image sequences in dynamic environment. Experimental results show that the features of dynamic objects can be correctly ignored by the proposed algorithm, and the feature matching accuracy can reach 98.8%, while maintaining the real-time property (the processing time of the same image with ORB is only 0.055ms longer).

Citation Download Citation

Shaojie Meng, Miaohua Huang, Yang Hou, and Yanyong Ren "Dynamic feature removal method based on relative geometry", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126103M (28 April 2023); https://doi.org/10.1117/12.2671163

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KEYWORDS

Feature extraction

Image processing

Cameras

Visualization

Detection and tracking algorithms

Engineering

Mathematical optimization

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