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This fish dataset currently consisting of 3,960 images collected from 468 species. This data consists of real-world images of fish captured in conditions defined as "controlled", "out-of-the-water" and "in-situ". The "controlled", images consists of fish specimens, with their fins spread, taken against a constant background with controlled illumination. The "in-situ" images are underwater images of fish in their natural habitat and so there is no control over background or illumination. The "out-of-the-water" images consist of fish specimens, taken out of the water with a varying background and limited control over the illumination conditions. A tight red bounding box is annotated around the fish. 

 

 
 

 

Dataset

This data are used for WACV 2014 paper "Local Inter-Session Variability Modelling for Object Classification".  Baseline classification results can also be found in this paper.

Download link can be used as follows (Dropbox):

https://www.dropbox.com/s/e2xya1pzr2tm9xr/QUT_fish_data.zip?dl=0

or (BaiduYun)

http://pan.baidu.com/s/1bp2Z06N

or

Send email to zongyuan ge  (z.ge@outlook.com or gzy555555@gmail.com) to request for the dataset. (respond in 24 hours)

Please cite this: 

@article{anantharajah2014local,
  title={Local inter-session variability modelling for object classification},
  author={Anantharajah, Kaneswaran and Ge, ZongYuan and McCool, Christopher and Denman, Simon and Fookes, Clinton B and Corke, Peter and Tjondronegoro, Dian W and Sridharan, Sridha},
  year={2014}
}

 

Credits

Dataset Authors

ZongYuan Ge              z.ge@outlook.com or gzy555555@gmail.com

Dr Chris Mccool           chris.mccool@nicta.com.au

Prof Peter Corke          peter.corke at qut.edu.au

 

Please direct any dataset queries or issues to ZongYuan Ge.