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.