Automated distance estimation for wildlife camera trapping

نویسندگان

چکیده

The ongoing biodiversity crisis calls for accurate estimation of animal density and abundance to identify sources decline effectiveness conservation interventions. Camera traps together with methods are often employed this purpose. necessary distances between camera observed animals traditionally derived in a laborious, fully manual or semi-automatic process. Both approaches require reference image material, which is both difficult acquire not available existing datasets. We propose automatic approach we call AUtomated DIstance esTimation (AUDIT) estimate camera-to-animal distances. leverage state-of-the-art relative monocular depth combine it novel alignment procedure metric AUDIT automated requires neither the comparison observations trap imagery images nor capturing material at all. therefore relieves biologists ecologists from significant workload. evaluate on zoo scenario dataset unseen during training where achieve mean absolute distance error over all instances only 0.9864 meters (REL) 0.113. code usage instructions https://github.com/PJ-cs/DistanceEstimationTracking

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ژورنال

عنوان ژورنال: Ecological Informatics

سال: 2022

ISSN: ['1878-0512', '1574-9541']

DOI: https://doi.org/10.1016/j.ecoinf.2022.101734