Collaborative Research: CoralReef3D - An open-source toolkit for underwater 3D ecosystem modeling and analysis

协作研究:CoralReef3D - 用于水下 3D 生态系统建模和分析的开源工具包

基本信息

  • 批准号:
    2316800
  • 负责人:
  • 金额:
    $ 70.12万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-15 至 2026-08-31
  • 项目状态:
    未结题

项目摘要

Coral reefs are one of the most diverse ecosystems on Earth, hosting at least 30% of all marine species. They generate almost $10 trillion USD per year globally and provide protein and income for more than 5% of humanity. Unfortunately, most coral reefs are in severe decline due to the climate change and local stressors. Some reefs, however, appear to be more resilient than others. We need to find and identify these reefs quickly to elucidate the factors that confer this resilience. Historically, the kinds of surveys required to locate and demonstrate resilience have been slow, expensive, and reliant on highly trained scientists. These traditional methods are too slow and too cumbersome to provide 21st Century solutions for our 21st Century challenges. In this project, advanced 3D computer vision and photogrammetric techniques will be assembled into a novel computational toolset called CoralReef3D, which will be made available to divers and coastal surveyors all over the world. This shareware will allow non-experts to create georeferenced (and therefore repeatable) 3D reef montages that can easily be assessed for benchmark studies on coral growth and survival. The impact of this research will be broadened by open-source software, online workshops, student training, and outreach activities involving museums and the general public.CoralReef3D is expected to bring forth significant advancements in underwater 3D measurements. During this research, novel water-refraction correction methods will be developed and incorporated into CoralReef3D. Correction for water-refraction distortions at the camera/water interface will allow production of accurate measurements of seascape montages. For instance, the program’s advanced capabilities for object-recognition and semantic-segmentation will allow it to generate on-image scales for linear or volumetric measurements. This will also enable precise calculations of ecosystem rugosity (topological complexity) and geomorphology in surveyed areas. By providing GPS information on all images, CoralReef3D can fate-track individual colonies and quantify ecosystem changes over time. Both controlled laboratory validation and in situ field validation will be conducted. Controlled laboratory validations will be performed in deep seawater tanks maintained by Reef Systems Coral Farm. In situ field validations will be performed in Hawaii and the Florida Keys along depth gradients. To shorten the learning curve normally associated with sophisticated image analysis programs, CoralReef3D will be extensively documented using both text and pictorial instructions. These technological advances will produce a benchmark method for 3D modeling of complex objects in water. CoralReef3D will empower both experts and non-specialists to make affordable, large-scale, and accurate assessments of rapidly-changing marine ecosystems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
珊瑚礁是地球上最少的生态系统之一,至少占所有海洋物种的30%。他们每年在全球每年产生近100万亿美元,并为人类的5%以上提供蛋白质和收入。不幸的是,由于气候变化和当地压力源,大多数珊瑚礁都在严重下降。但是,有些珊瑚礁似乎比其他珊瑚礁更具抵抗力。我们需要迅速找到并识别这些礁石,以阐明赋予这种弹性的因素。从历史上看,定位和证明弹性所需的调查种类缓慢,昂贵且可靠,对训练有素的科学家来说是可靠的。这些传统方法太慢,太麻烦了,无法为我们21世纪的挑战提供21世纪的解决方案。在这个项目中,先进的3D计算机视觉和摄影测量技术将组装成一个名为Coralreef3d的新型计算工具集,该工具集将用于世界各地的潜水员和沿海测量师。该共享软件将允许非专家创建(因此可重复)3D礁蒙太奇,可以轻松评估有关珊瑚生长和生存的基准研究。这项研究的影响将通过开源软件,在线研讨会,学生培训和涉及博物馆和公共公众的外展活动来扩展。Coralreef3D有望在水下3D测量中带来重大进步。在这项研究中,将开发出新的水疗法校正方法并将其纳入Coralreef3d。对摄像机/水接口处水分扭曲的纠正将允许生产准确的海景单曲测量。例如,该程序用于对象识别和语义细分的高级功能将使其能够生成线性或体积测量的内图像量表。这还将实现对被调查区域的生态系统皱纹(拓扑复杂性)和地貌学的精确计算。通过在所有图像上提供GPS信息,Coralreef3D可以命运单个菌落并量化生态系统随时间变化。将进行受控实验室验证和原位现场验证。受控实验室验证将在珊瑚礁系统珊瑚农场维护的深海水箱中进行。原位现场验证将在夏威夷和深度梯度沿佛罗里达密钥进行。为了缩短通常与复杂的图像分析程序相关的学习曲线,Coralreef3d将使用文本和绘画说明进行广泛记录。这些技术进步将产生一种基准方法,用于对水中的复杂物体进行3D建模。 Coralreef3D将使专家和非专家们能够对快速变化的海洋生态系统进行负担得起的,大规模和准确的评估。这项奖项反映了NSF的法定任务,并通过使用基金会的知识分子优点和更广泛的影响审查标准来通过评估来诚实地支持。

项目成果

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Rongjun Qin其他文献

Bundle adjustment with motion constraints for uncalibrated multi-camera systems at the ground level
地面未校准多摄像机系统的运动约束束调整
Stereo Dense Image Matching by Adaptive Fusion of Multiple-Window Matching Results
通过多窗口匹配结果的自适应融合进行立体密集图像匹配
  • DOI:
    10.3390/rs12193138
  • 发表时间:
    2020-09
  • 期刊:
  • 影响因子:
    5
  • 作者:
    Yilong Han;Wei Liu;Xu Huang;Shugen Wang;Rongjun Qin
  • 通讯作者:
    Rongjun Qin
Fighting Illicit Trafficking of Cultural Goods—The ENIGMA Project
打击非法贩运文化产品——ENIGMA 项目
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Henrique Lorenzo;Fabio Remondino;Magaly Koch;Rongjun Qin;P. Patias;C. Georgiadis
  • 通讯作者:
    C. Georgiadis
A Flexible Inference Machine for Global Alignment of Wall Openings
用于墙壁开口全局对齐的灵活推理机
  • DOI:
    10.3390/rs12121968
  • 发表时间:
    2020-06
  • 期刊:
  • 影响因子:
    5
  • 作者:
    Jiaqiang Li;Biao Xiong;Rongjun Qin;Armin Gruen
  • 通讯作者:
    Armin Gruen
A Local Distinctive Features Matching Method for Remote Sensing Images with Repetitive Patterns
一种重复模式遥感影像局部特征匹配方法

Rongjun Qin的其他文献

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