A Benchmark for Maritime Object Detection with Centernet on an Improved Dataset, ABOships-PLUS

Bogdan Iancu*, Jesper Winsten, Valentin Soloviev, Johan Lilius

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArtikkeliTieteellinenvertaisarvioitu

36 Lataukset (Pure)

Abstrakti

Object detection from waterborne imagery is an essential aspect in maritime traffic management, navigation safety and coastal security. Building efficient autonomous systems, which can take decisions in critical situations, requires an integration of complex object detectors in real time. Object detectors trained on generic datasets often give unsatisfactory results in complex scenarios like the maritime environment, since only a fraction of their images contain maritime vessels. Publicly available domain-specific datasets are scarce, and they are limited in the number of images and annotations. Compared to object detection in applications such as autonomous vehicles, maritime vessel detection is considerably reduced in computer vision research. This creates a deficit in exhaustive benchmarking studies for maritime detection datasets. To bridge this gap, we relabel the ABOships dataset and benchmark a state-of-the-art center-based detector, Centernet, on the newly relabeled dataset, ABOships-PLUS. We explore its performance under different feature extractors, and investigate the effect of object size and inter-class variation on detection accuracy. The reported benchmarking illustrates that the ABOships-PLUS dataset is adequate to use in supervised domain adaptation. The experimental results show that Centernet with DLA (Deep Layer Aggregation) as a feature extractor achieved the highest accuracy in detecting maritime objects overall (with mean average precision 74.4%).
AlkuperäiskieliEnglanti
Artikkeli1638
Sivumäärä18
JulkaisuJournal of Marine Science and Engineering
Vuosikerta11
Numero9
DOI - pysyväislinkit
TilaJulkaistu - 22 elok. 2023
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

Sormenjälki

Sukella tutkimusaiheisiin 'A Benchmark for Maritime Object Detection with Centernet on an Improved Dataset, ABOships-PLUS'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

Viittausmuodot