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Are object detection assessment criteria ready for maritime computer vision?

Permanent lenke
https://hdl.handle.net/10037/18161
DOI
https://doi.org/10.1109/TITS.2019.2954464
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article.pdf (9.813Mb)
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Dato
2019-11-25
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Forfatter
Prasad, Dilip K.; Dong, Huixu; Rajan, Deepu; Quek, Chai
Sammendrag
Maritime vessels equipped with visible and infrared cameras can complement other conventional sensors for object detection. However, application of computer vision techniques in maritime domain received attention only recently. The maritime environment offers its own unique requirements and challenges. Assessment of the quality of detections is a fundamental need in computer vision. However, the conventional assessment metrics suitable for usual object detection are deficient in the maritime setting. Thus, a large body of related work in computer vision appears inapplicable to the maritime setting at the first sight. We discuss the problem of defining assessment metrics suitable for maritime computer vision. We consider new bottom edge proximity metrics as assessment metrics for maritime computer vision. These metrics indicate that existing computer vision approaches are indeed promising for maritime computer vision and can play a foundational role in the emerging field of maritime computer vision.
Beskrivelse
© 2019 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.
Forlag
Institute of Electrical and Electronics Engineers (IEEE)
Sitering
Prasad DK, Dong, Rajan, Quek. Are object detection assessment criteria ready for maritime computer vision?. IEEE transactions on intelligent transportation systems (Print). 2019
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  • Artikler, rapporter og annet (informatikk) [481]
© 2019 IEEE

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