An Image Processing Pipeline for Camera Trap Time-Lapse Recordings

TL;DR

This paper introduces an open-source image processing pipeline that leverages machine learning for efficient analysis of camera trap videos, aiding ecological research.

Contribution

It presents a novel pipeline integrating machine learning models for video segmentation and animal re-identification in camera trap data.

Findings

Improved efficiency in analyzing large camera trap datasets

Successful application in a year-long ecological study

Enhanced accuracy in animal re-identification

Abstract

A new open-source image processing pipeline for analyzing camera trap time-lapse recordings is described. This pipeline includes machine learning models to assist human-in-the-loop video segmentation and animal re-identification. We present some performance results and observations on the utility of this pipeline after using it in a year-long project studying the spatial ecology and social behavior of the gopher tortoise.