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Dolphin fin pose correction using ICP in application to photo-identification

机译:使用ICP的海豚鳍姿态校正在光识别中的应用

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Photo-identification of dolphin individuals is a commonly used technique in ecological sciences to monitor state and health of individuals, as well as to study the social structure and distribution of a population. Uniqueness of some forms of damage sustained by the trailing edge of the dorsal fin throughout an individual's life allows it to be used to identify the individual. Traditional photo-identification involves a laborious manual process of matching each dolphin fin photograph captured in the field to a catalogue of known individuals. A number of efforts have been made in the past to automate this process through the use of digital image processing; however, none of them correct for the different fin orientations (3D pose) prior to performing matching in a robust way. This paper provides an overview of these existing methods and offers a novel approach of utilising the iterative closest point (ICP) algorithm for performing the projective registration of two fin shapes and shows that this proposed method is robust to segmentation noise, partial occlusions and new nicks and notches appearing since last encounter.
机译:海豚个体的光识别是生态科学中用于监视个体状态和健康以及研究人口的社会结构和分布的一种常用技术。在个体的整个生命周期中,背鳍后缘承受的某些形式的损伤的独特性使其可以用来识别个体。传统的照片识别涉及费力的手动过程,该过程将在现场捕获的每只海豚鳍照片与已知人员的目录进行匹配。过去,通过使用数字图像处理,为使该过程自动化,已经进行了许多努力。但是,在以稳健的方式执行匹配之前,它们都无法针对不同的鳍片方向(3D姿势)进行校正。本文提供了这些现有方法的概述,并提供了一种利用迭代最近点(ICP)算法执行两个鳍形状的投影配准的新颖方法,并显示了该方法对分割噪声,部分遮挡和新刻痕具有鲁棒性和自上次相遇以来出现的缺口。

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