@InProceedings{7362362,
  author = {K. Nasreddine and A. Benzinou},
  booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},
  title = {Shape-based fish recognition via shape space},
  year = {2015},
  pages = {145-149},
  abstract = {Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we introduce a preliminary step of pose estimation for accelerating the processing time. We then show that shape geodesics may also be used for outline-based fish recognition. Experiments conducted on the SQUID database which is used as a benchmark to evaluate fish shape recognition, show (1) a reduction in computation time of a factor of ten in average, and (2) the outperformance of the proposed scheme compared to previous methods.},
  keywords = {aquaculture;image classification;image registration;marine engineering;pose estimation;shape-based fish recognition;shape space;automatic fish recognition;marine scientists;fish outline;pattern recognition;signal registration;shape geodesics;pose estimation;outline-based fish recognition;SQUID database;fish shape recognition;Shape;Databases;SQUIDs;Robustness;Estimation;Benchmark testing;Fish recognition;outline;shape;geodesics},
  doi = {10.1109/EUSIPCO.2015.7362362},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570104943.pdf},
}

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In this paper, we introduce a preliminary step of pose estimation for accelerating the processing time. We then show that shape geodesics may also be used for outline-based fish recognition. 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Benzinou},\n booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},\n title = {Shape-based fish recognition via shape space},\n year = {2015},\n pages = {145-149},\n abstract = {Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we introduce a preliminary step of pose estimation for accelerating the processing time. We then show that shape geodesics may also be used for outline-based fish recognition. 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