The footprint identification technology (FIT) is a tool for monitoring endangered species.
This technique was developed by WildTrack, as a translation of indigenous tracking expertise. From digital images of footprints, FIT can identify species, individuals, age-class and sex.
In 2020 we have augmented FIT with the power of artificial intelligence (AI) to classify large volumes of footprint data more rapidly. We were honoured to win the Hal R. Varian Capstone award from U C Berkeley for this work.
This video shows how FIT works step-by-step:
From: Jewell, Z. C., Alibhai, S. K., Weise, F., Munro, S., Van Vuuren, M., & Van Vuuren, R. (2016). Spotting Cheetahs: Identifying Individuals by Their Footprints. Journal of visualized experiments: JoVE, (111).
The two main steps in the FIT procedure are:
1. The capture of footprints and conversion of a footprint into a geometric profile
2. Data analyses for the purpose of classification.
Identifying footprints (tracks) is in some ways analogous to fingerprinting, but much more complex! Firstly, each species has a different foot anatomy so requires a customized species algorithm – the set of variables which determine the characteristics of that species. Secondly, within each species, each individual has its own unique foot characteristics, analogous to our fingerprints. Thirdly, each individual has four feet and it is necessary to identify which track results from each foot in order to standardize the analytical procedures.
Lastly, each time the individual puts a foot on the ground, it leaves a slightly different track. This is determined by many factors, including the gait of the animal, substrate type, moisture levels and weather conditions. In order to account for the variation of tracks along the same trail (i.e. made by the same animal), we collect 6 – 8 different tracks from each trail.