...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Experimental Marine Biology and Ecology >HotSpotter: Using a computer-driven photo-id application to identify sea turtles
【24h】

HotSpotter: Using a computer-driven photo-id application to identify sea turtles

机译：热点：使用计算机驱动的照片ID应用程序来识别海龟

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Photo identification (PID) in animal studies has been a widely used method for identifying individuals of many species based on unique natural markings and patterns. The use of PID has facilitated investigations in which residency, home ranges, and growth rates have been assessed. However, many PID studies in the past have relied heavily on manual photo matching. More recently, computer-assisted PID programs have been used to identify individuals of different sea turtle species, and reduced time investment in identifying individuals within specific populations. Still, some computer-based PID programs require significant time investment in ensuring photos are captured at consistent angles and lighting conditions, pre-processing image manipulations, and post-processing manual matching confirmation of potential matches provided by the program. For PID to be an effective time and money saving mechanism for wildlife research and conservation, these common drawbacks need to be addressed with a computer-assisted PID program that reduces manipulation and time investment burden, and consistently provides accurate and reliable results. In this study, we evaluated the accuracy of matching individual face images using the HotSpotter (HS) PID program by building a database of 2136 images of hawksbill (Eretmochelys imbricata) turtles, then querying the database with 158 new images to find matches for individual turtles. Overall, we found that with almost no pre-processing manipulation, and with images from highly variable underwater conditions, qualities, and angles, HS correctly matched individuals in the first choice 80% of the time, increasing to 91% in the first six choices. When assessing in-water images only, accuracy for matching increased from 84% in the first choice, to 94% by the sixth choice. We suggest that the integration of HS technology into a global, web-based PID system will increase the ability to remotely identify individual marine organisms on a global scale, and improve usability for community scientists who may have little to no technical training.
机译：动物研究中的照片鉴定（PID）是一种广泛使用的方法，用于根据独特的自然标记和模式识别许多物种的个体。 PID的使用促进了居住，家庭范围和增长率的调查。然而，过去的许多PID研究已经依赖于手动照片匹配。最近，计算机辅助的PID程序已被用于识别不同海龟物种的个体，并减少了在特定人群中识别个人的时间投资。尽管如此，一些基于计算机的PID程序需要大量的时间投资在确保在一致的角度和照明条件，预处理图像操纵以及程序提供的潜在匹配的后处理手册匹配的照片中的投资。对于PID成为野生动物研究和保护的有效时间和省钱机制，需要通过计算机辅助的PID程序来解决这些共同的缺点，可降低操纵和时间投资负担，并始终如一地提供准确可靠的结果。在这项研究中，我们通过构建了2136张Hawksbill（Eretmochice Imbricata）海龟的数据库，评估了使用热点（HS）PID程序匹配个体面部图像的准确性，然后用158个新图像查询数据库以查找单个乌龟的匹配。总体而言，我们发现，几乎没有预处理操作，并且在高度可变的水下条件，品质和角度的图像中，HS在第一个选择中正确匹配个体的时间，在前六个选择中增加到91％ 。仅在评估水中图像时，匹配的准确性从第一选择的84％增加到94％，第六选择。我们建议将HS技术集成到全球性的网络的PID系统将增加能够在全球范围内远程识别单个海洋生物，并提高社区科学家的可用性，这些科学家可能没有技术培训。

著录项

  • 来源
    《Journal of Experimental Marine Biology and Ecology》 |2021年第2期|151490.1-151490.11|共11页
  • 作者

    Dunbar Stephen G.; Anger Edward C.; Parham Jason R.; Kingen Colin; Wright Marsha K.; Hayes Christian T.; Safi Shahnaj; Holmberg Jason; Salinas Lidia; Baumbach Dustin S.;

  • 作者单位

    Loma Linda Univ Dept Earth & Biol Sci Marine Res Grp Loma Linda CA 92350 USA|Protect Turtle Ecol Ctr Training Outreach Res Inc ProTECTOR Inc Loma Linda CA 92350 USA|Protect Turtle Ecol Ctr Training Outreach Res Hon ProTECTOR Honduras Tegucigalpa Honduras;

    ScubaTed Roatan Honduras;

    WildMe Portland OR 97217 USA|Rensselaer Polytech Inst Troy NY 12180 USA;

    WildMe Portland OR 97217 USA;

    Loma Linda Univ Dept Earth & Biol Sci Marine Res Grp Loma Linda CA 92350 USA|Protect Turtle Ecol Ctr Training Outreach Res Inc ProTECTOR Inc Loma Linda CA 92350 USA;

    Loma Linda Univ Dept Earth & Biol Sci Marine Res Grp Loma Linda CA 92350 USA|Protect Turtle Ecol Ctr Training Outreach Res Inc ProTECTOR Inc Loma Linda CA 92350 USA|Univ Southern Mississippi Sch Ocean Sci & Engn Div Coastal Sci Ocean Springs MS 39564 USA;

    Loma Linda Univ Sch Publ Hlth Loma Linda CA 92350 USA;

    WildMe Portland OR 97217 USA;

    Protect Turtle Ecol Ctr Training Outreach Res Inc ProTECTOR Inc Loma Linda CA 92350 USA|Protect Turtle Ecol Ctr Training Outreach Res Hon ProTECTOR Honduras Tegucigalpa Honduras;

    Loma Linda Univ Dept Earth & Biol Sci Marine Res Grp Loma Linda CA 92350 USA|Protect Turtle Ecol Ctr Training Outreach Res Inc ProTECTOR Inc Loma Linda CA 92350 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Marine turtles; Photo identification; Computer-automated algorithms; Sea turtle database management;

    机译：海龟;照片识别;计算机自动化算法;海龟数据库管理;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号