Florida Wildlife Camera Trap Dataset
This dataset helps biologists and ecologists by providing a challenging resource for species classification, though it is incremental as it adds to existing camera trap datasets.
The authors introduced a wildlife camera trap dataset from Florida with 104,495 images to address the lack of rich data for ecological studies, and experiments with ResNet-50 showed it can advance wildlife statistical modeling.
Trail camera imagery has increasingly gained popularity amongst biologists for conservation and ecological research. Minimal human interference required to operate camera traps allows capturing unbiased species activities. Several studies - based on human and wildlife interactions, migratory patterns of various species, risk of extinction in endangered populations - are limited by the lack of rich data and the time-consuming nature of manually annotating trail camera imagery. We introduce a challenging wildlife camera trap classification dataset collected from two different locations in Southwestern Florida, consisting of 104,495 images featuring visually similar species, varying illumination conditions, skewed class distribution, and including samples of endangered species, i.e. Florida panthers. Experimental evaluations with ResNet-50 architecture indicate that this image classification-based dataset can further push the advancements in wildlife statistical modeling. We will make the dataset publicly available.