Please use this identifier to cite or link to this item:
|Title:||Object detection in a maritime environment : performance evaluation of background subtraction methods||Authors:||Prasath, Chandrashekar Krishna
Prasad, Dilip Kumar
|Keywords:||Engineering::Computer science and engineering
|Issue Date:||2018||Source:||Prasad, D. K., Prasath, C. K., Rajan, D., Rachmawati, L., Rajabally, E., & Quek, C. (2019). Object detection in a maritime environment : performance evaluation of background subtraction methods. IEEE Transactions on Intelligent Transportation Systems, 20(5), 1787-1802. doi:10.1109/TITS.2018.2836399||Series/Report no.:||IEEE Transactions on Intelligent Transportation Systems||Abstract:||This paper provides a benchmark of the performance of 23 classical and state-of-the-art background subtraction (BS) algorithms on visible range and near infrared range videos in the Singapore Maritime dataset. Importantly, our study indicates the limitations of the conventional performance evaluation criteria for maritime vision and proposes new performance evaluation criteria that is better suited to this problem. This paper provides insight into the specific challenges of BS in maritime vision. We identify four open challenges that plague BS methods in maritime scenario. These include spurious dynamics of water, wakes, ghost effect, and multiple detections. Poor recall and extremely poor precision of all the 23 methods, which have been otherwise successful for other challenging BS situations, allude to the need for new BS methods custom designed for maritime vision.||URI:||https://hdl.handle.net/10356/84193
|ISSN:||1524-9050||DOI:||http://dx.doi.org/10.1109/TITS.2018.2836399||Rights:||© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TITS.2018.2836399.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Journal Articles|
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.