ThruTracker: Open-Source Software for 2-D and 3-D Animal Video Tracking

Aj, Corcoran; Mr, Schirmacher; Black, Emily; Hedrick, Tyson L.

doi:10.1101/2021.05.12.443854

Cited by 11 publications

(7 citation statements)

References 44 publications

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“…However, the software has not been maintained and cannot be used with current thermal imaging cameras. Recent advances in machine learning approaches and image analysis toolboxes have resulted in several algorithms for tracking the movements of animals [5][6][7][8][9][10], yet these products have not been widely used by users outside of academia, largely due to the perceived training required to run the software; as a result, the few thermal imagery population estimations conducted by biologists outside of academic institutions are often achieved with manual counts of video samples, which is a time-intensive process [M. Armstrong, personal communication; V. Kuczynska, personal communication; N. Sharp, personal communication].…”

Section: Introductionmentioning

confidence: 99%

BatCount: A software program to count moving animals

et al. 2023

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One of the biggest challenges with species conservation is collecting accurate and efficient information on population sizes, especially from species that are difficult to count. Bats worldwide are declining due to disease, habitat destruction, and climate change, and many species lack reliable population information to guide management decisions. Current approaches for estimating population sizes of bats in densely occupied colonies are time-intensive, may negatively impact the population due to disturbance, and/or have low accuracy. Research-based video tracking options are rarely used by conservation or management agencies for animal counting due to the perceived training and elevated operating costs. In this paper, we present BatCount, a free software program created in direct consultation with end-users designed to automatically count bats emerging from cave roosts (historical populations 20,000–250,000) with a streamlined and user-friendly interface. We report on the software package and provide performance metrics for different recording habitat conditions. Our analysis demonstrates that BatCount is an efficient and reliable option for counting bats in flight, with performance hundreds of times faster than manual counting, and has important implications for range- and species-wide population monitoring. Furthermore, this software can be extended to count any organisms moving across a camera including birds, mammals, fish or insects.

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Section: Introductionmentioning

confidence: 99%

BatCount: A software program to count moving animals

et al. 2023

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“…Over a decade ago, the U.S. Army Corps of Engineers created proprietary software ("T 3 ") integrated into a camera system to count bats from thermal imagery (5), but the software has not been maintained and cannot be used with current thermal imaging cameras. Recent advances in machine learning approaches and image analysis toolboxes have resulted in several algorithms for tracking the movements of animals (6)(7)(8)(9)(10)(11), yet these products have not been widely used by users outside of academia, largely due to the perceived training required to run the software (M. Armstrong, personal communication; V. Kuczynska, personal communication; N. Sharp, personal communication). As a result, the few thermal imagery population estimations conducted by biologists outside of academic institutions are achieved with manual counts of video samples, which is a time-intensive process.…”

Section: Introductionmentioning

confidence: 99%

BatCount: A software program to count moving animals

Bentley

Kuczynska

Eddington

et al. 2022

Preprint

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One of the biggest challenges with species conservation is collecting accurate and efficient information on population sizes, especially from species that are difficult to count. Bats worldwide are declining due to disease, habitat destruction, and climate change, and many species lack reliable population information to guide management decisions. Current approaches for estimating population sizes of bats in densely occupied colonies are time-intensive, may negatively impact the population due to disturbance, and or have low accuracy. Research-based video tracking options are rarely used by conservation or management agencies for animal counting due to the perceived training required to operate. In this paper, we present BatCount, a free software program created in direct consultation with end-users designed to automatically count aggregations of bats at cave roosts with a streamlined and user-friendly interface. We report on the software package and provide performance metrics for different recording habitat conditions. Our analysis demonstrates that BatCount is an efficient and reliable option for counting bats in flight and has important implications for range- and species-wide population monitoring. Furthermore, this software can be extended to count any organisms moving across a camera including birds, mammals, fish or insects.

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“…Several recent technological advances have enabled researchers to tackle scientific questions on locomotion in a more efficient way. Firstly, the past few years have brought huge leaps in terms of computer vision, deep learning, and thereby semi-automatic video digitization methods (Corcoran et al, 2021; Jackson et al, 2016; Karashchuk et al, 2021; Mathis et al, 2020; Mielke et al, 2020). These tools typically require a manually digitized subset of the data as the “training set” for a neural network, which is then able to digitize further videos in high through-put, hopefully with reasonable accuracy.…”

Section: Introductionmentioning

confidence: 99%

A Workflow for High Through-Put, High Precision Livestock Diagnostic Screening of Locomotor Kinematics

Mielke

Ginneken

Aerts

2022

Preprint

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In the study of vertebrate locomotion, kinematic measures of gait, dynamic posture, and coordination often change when comparing subjects of different body mass, size, and age. Is it, conversely, possible to infer subject characteristics from the kinematic measures? For this study, piglets (Sus domesticus) were filmed from lateral perspective during their first ten hours of life, an age at which body mass and size have major consequences for survival. We then apply deep learning methods for point digitization (DeepLabCut), calculate joint angle profiles, and apply an information-preserving transfromation (Fourier series) to retrieve a multivariate kinematic data set. We train a probabilistic model to predict subject characteristics from kinematics. The model infers subject characteristics accurately for strides from piglets of normal birth weight (i.e. the category it was trained on), but surprisingly predicts the body mass and size of low birth weight piglets (which were left out of training, out-of-sample prediction) to be "normal". The discrepancies between prediction and observation confirm that dynamic posture and coordination are unaffected by lower birth weight and lower size, which is evidence that low birth weight does not imply locomotor deficits. However, the age of some (but not all) low birth weight individuals is underestimated, supporting the hypothesis that these piglets experience a delay in locomotor maturation.

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ThruTracker: Open-Source Software for 2-D and 3-D Animal Video Tracking

Cited by 11 publications

References 44 publications

BatCount: A software program to count moving animals

BatCount: A software program to count moving animals

BatCount: A software program to count moving animals

A Workflow for High Through-Put, High Precision Livestock Diagnostic Screening of Locomotor Kinematics

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