Feature Tracking for Target Identification in Acoustic Image Sequences

Jue Gao, Ya Gu, Peiyi Zhu and Jing Na

Complexity, 2021, vol. 2021, 1-11

Abstract: This paper proposes underwater target identification with local features and a feature tracking algorithm for acoustic image sequences. Feature detectors and descriptors are key to feature tracking. Their performance in underwater scene is evaluated by the change of multitarget parameters. A comprehensive quantitative investigation into the performance of feature tracking is thereby presented. Experimental results confirm that the proposed algorithm can accurately track potential targets and determine whether the potential targets are static targets, dynamic targets, or false alarms according to the tracking trajectories and statistical data.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8885821

DOI: 10.1155/2021/8885821

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