Through Hawks' Eyes: Synthetically Reconstructing the Visual Field of a Bird in Flight.

IF 11.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Sofía Miñano, Stuart Golodetz, Tommaso Cavallari, Graham K Taylor
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引用次数: 3

Abstract

Birds of prey rely on vision to execute flight manoeuvres that are key to their survival, such as intercepting fast-moving targets or navigating through clutter. A better understanding of the role played by vision during these manoeuvres is not only relevant within the field of animal behaviour, but could also have applications for autonomous drones. In this paper, we present a novel method that uses computer vision tools to analyse the role of active vision in bird flight, and demonstrate its use to answer behavioural questions. Combining motion capture data from Harris' hawks with a hybrid 3D model of the environment, we render RGB images, semantic maps, depth information and optic flow outputs that characterise the visual experience of the bird in flight. In contrast with previous approaches, our method allows us to consider different camera models and alternative gaze strategies for the purposes of hypothesis testing, allows us to consider visual input over the complete visual field of the bird, and is not limited by the technical specifications and performance of a head-mounted camera light enough to attach to a bird's head in flight. We present pilot data from three sample flights: a pursuit flight, in which a hawk intercepts a moving target, and two obstacle avoidance flights. With this approach, we provide a reproducible method that facilitates the collection of large volumes of data across many individuals, opening up new avenues for data-driven models of animal behaviour.

Supplementary information: The online version contains supplementary material available at 10.1007/s11263-022-01733-2.

Abstract Image

Abstract Image

Abstract Image

透过鹰的眼睛:综合重建飞行中的鸟的视野。
猛禽依靠视觉来执行飞行动作,这是它们生存的关键,比如拦截快速移动的目标或在杂乱中导航。更好地理解视觉在这些动作中所扮演的角色不仅与动物行为领域相关,而且也可以应用于自主无人机。在本文中,我们提出了一种使用计算机视觉工具来分析主动视觉在鸟类飞行中的作用的新方法,并展示了它在回答行为问题方面的应用。将哈里斯鹰的动作捕捉数据与环境的混合3D模型相结合,我们渲染了RGB图像、语义地图、深度信息和光流输出,这些输出表征了鸟在飞行中的视觉体验。与之前的方法相比,我们的方法允许我们考虑不同的相机模型和替代凝视策略,以进行假设检验,允许我们考虑鸟的整个视野的视觉输入,并且不受技术规格和头戴式相机的性能的限制,这种相机足够轻,可以附着在飞行中的鸟的头上。我们提供了三个飞行样本的飞行员数据:一个是追击飞行,其中鹰拦截了一个移动目标,还有两个是避障飞行。通过这种方法,我们提供了一种可重复的方法,可以方便地收集许多个体的大量数据,为数据驱动的动物行为模型开辟了新的途径。补充资料:在线版本提供补充资料,网址为10.1007/s11263-022-01733-2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Computer Vision
International Journal of Computer Vision 工程技术-计算机:人工智能
CiteScore
29.80
自引率
2.10%
发文量
163
审稿时长
6 months
期刊介绍: The International Journal of Computer Vision (IJCV) serves as a platform for sharing new research findings in the rapidly growing field of computer vision. It publishes 12 issues annually and presents high-quality, original contributions to the science and engineering of computer vision. The journal encompasses various types of articles to cater to different research outputs. Regular articles, which span up to 25 journal pages, focus on significant technical advancements that are of broad interest to the field. These articles showcase substantial progress in computer vision. Short articles, limited to 10 pages, offer a swift publication path for novel research outcomes. They provide a quicker means for sharing new findings with the computer vision community. Survey articles, comprising up to 30 pages, offer critical evaluations of the current state of the art in computer vision or offer tutorial presentations of relevant topics. These articles provide comprehensive and insightful overviews of specific subject areas. In addition to technical articles, the journal also includes book reviews, position papers, and editorials by prominent scientific figures. These contributions serve to complement the technical content and provide valuable perspectives. The journal encourages authors to include supplementary material online, such as images, video sequences, data sets, and software. This additional material enhances the understanding and reproducibility of the published research. Overall, the International Journal of Computer Vision is a comprehensive publication that caters to researchers in this rapidly growing field. It covers a range of article types, offers additional online resources, and facilitates the dissemination of impactful research.
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