1. Laboratoire d''Instrumentation, Image et Spectroscopie, Institut National Polytechnique Félix Houphouët-Boigny, BP 1093 Yamoussoukro, Côte d''Ivoire;2. Université Lille, CNRS, UMR 8524-Laboratoire Paul Painlevé, INRIA-MODAL, F-59000 Lille, France;1. University of Pretoria, Pretoria, South Africa;2. Defence, Peace, Safety and Security, Council of Scientific and Industrial Research, Pretoria, South Africa;3. Air Force Research Lab, Rome, NY, USA
Abstract:
The monitoring of wildlife populations is of growing importance due to the worldwide endangerment of many species, global climate change, and land cover change. Wildlife monitoring by camera traps is an established and non-invasive standard approach to quantify species diversity, estimate occupancy and relative abundance and track animal behaviour in 24/7 documentation. We propose a novel wildlife-specific 3D multi-object tracking workflow using inexpensive stereo camera traps. By embedding carefully efficient 2D methods into the overall 3D workflow, we avoid, on the one hand, costly processing of complex 3D data structures, i.e., 3D point clouds but on the other hand outperform significantly typical 2D tracking approaches with our overall 3D workflow in terms of international established multi-object tracking metrics, i.e., with respect to the reliability and accuracy of the tracking results. The code is available at https://github.com/m-klasen/3d_wildlife-tracking
