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Automated extraction of bank angles from bird-borne video footage using open-source software
Automated extraction of bank angles from bird-borne video footage using open-source software
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Automated extraction of bank angles from bird-borne video footage using open-source software
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Automated extraction of bank angles from bird-borne video footage using open-source software
Automated extraction of bank angles from bird-borne video footage using open-source software

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Automated extraction of bank angles from bird-borne video footage using open-source software
Automated extraction of bank angles from bird-borne video footage using open-source software
Journal Article

Automated extraction of bank angles from bird-borne video footage using open-source software

2019
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Overview
The use of miniaturized video cameras to study the at-sea behavior of flying seabirds has increased in recent years. These cameras allow researchers to record several behaviors that were not previously possible to observe. However, video recorders produce large amounts of data and videos can often be time-consuming to analyze. We present a new technique using open-source software to extract bank angles from bird-borne video footage. Bank angle is a key facet of dynamic soaring, which allows albatrosses and petrels to efficiendy search vast areas of ocean for food. Miniaturized video cameras were deployed on 28 Wandering Albatrosses (Diomedea exulans) on Marion Island (one of the two Prince Edward Islands) from 2016 to 2018. The OpenCV library for the Python programming language was used to extract the angle of the horizon relative to the bird's body (= bank angle) from footage when the birds were flying using a series of steps focused on edge detection. The extracted angles were not significantly different from angles measured manually by three independent observers, thus being a valid method to measure bank angles. Image quality, high wind speeds, and sunlight all influenced the accuracy of angle estimates, but post-processing eliminated most of these errors. Birds flew most often with cross-winds (58%) and tailwinds (39%), resulting in skewed distributions of bank angles when birds turned into the wind more often. Higher wind speeds resulted in extreme bank angles (maximum observed was 94°). We present a novel method for measuring postural data from seabirds that can be used to describe the fine-scale movements of the dynamic-soaring cycle. Birds appeared to alter their bank angle in response to varying wind conditions to counter wind drift associated with the prevailing westerly winds in the Southern Ocean. These data, in combination with fine-scale positional data, may lead to new insights into dynamic-soaring flight. El uso de cámaras de video en miniatura para estudiar el comportamiento en el mar de las aves marinas durante el vuelo ha aumentado en los últimos años. Estas cámaras permiten a los investigadores registrar varios comportamientos que antes no eran posible de observar. Sin embargo, las grabadoras de video producen grandes cantidades de datos y los videos a menudo pueden llevar mucho tiempo analizarlos. Presentamos una nueva técnica que utiliza software de código abierto para extraer los ángulos de inclinación de imágenes de videos. El ángulo de inclinación es una faceta clave para la dinámica de planeo, que permite a los albatros y petreles buscar alimentos en vastas áreas del océano. Las cámaras de video en miniatura se colocaron en 28 albatros errantes (Diomedea exulans) en la isla Marion (una de las dos islas del Príncipe Eduardo) entre 2016 y 2018. La biblioteca OpenCV para el lenguaje de programación Python se usó para extraer el ángulo del horizonte en relación con el cuerpo del ave (= ángulo de inclinación) del video cuando las aves volaban usando una serie de pasos centrados en la detección de bordes. Los ángulos extraídos no fueron significativamente diferentes de los ángulos medidos manualmente por tres observadores independientes, por lo que es un método válido para medir ángulos de banco. La calidad de la imagen, las altas velocidades del viento y la luz solar influyeron en la precisión de las estimaciones de ángulo, pero el procesamiento posterior eliminó la mayoría de estos errores. Las aves volaron con mayor frecuencia con vientos cruzados (58%) y vientos de cola (39%), lo que resulta en una distribución sesgada de los ángulos de las orillas cuando las aves giraron hacia el viento con más frecuencia. Las velocidades más altas del viento dieron como resultado ángulos extremos de inclinación (el máximo observado fue 94°). Presentamos un método novedoso para medir datos de posturas de aves marinas que se pueden usar para describir los movimientos a escala fina del ciclo dinámico del vuelo de planeo. Las aves parecen alterar su ángulo de inclinación en respuesta a las condiciones variables del viento para contrarrestar la deriva del viento asociada con los vientos predominantes del oeste en el Océano Austral. Estos datos, en combinación con datos posicionales a escala fina, pueden conducir a nuevas ideas sobre el vuelo de planeo dinámico.