Collaborative Research: NRI: INT: Dense 3D Reconstruction of Dynamic Actors in Natural Environments using Multiple Flying Cameras
合作研究:NRI:INT:使用多个飞行摄像机对自然环境中的动态演员进行密集 3D 重建
基本信息
- 批准号:2024173
- 负责人:
- 金额:$ 86.02万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
While large-scale multi-camera domes have been developed for data collection in controlled laboratory settings it is not possible to achieve a similar level of measurement quality outdoors where there is much potential benefit to such data collection. For example, use of such measurements include the body dynamics of a running cheetah, or people, or analyzing herding behaviors of animals or birds. This leads to scientists relying on extremely inefficient and dangerous data collection methods. For example, biologists studying the behaviors of wild animals try to predict where the animals will be and place some cameras which only give some limited data at specific locations. This project addresses such challenges by exploring the research of methods and development of a large-scale data collection tool for high-resolution and multi-viewpoint visual recording and motion analysis of natural group behaviors (e.g., herds of animals or groups of people) in-the-wild over very large environments (e.g., desert plains or mountain sides) using a team of flying robots. This project develops computational models that integrate the fundamentals of computer vision and multi-agent control to measure the group of actors in 3D. Through the development of this system, this project will make major advances in technology at the intersection of perception and control that include: (1) a new study of methods for precise, rapid, and robust target motion forecasting and relative state estimation that estimates the 3D motion of the robots and actors quickly with strong uncertainty estimates; (2) a new decomposition of the perception-aware multi-objective multi-UAV safe motion planning problem, that allows long-term planning based on consistent actor forecasting uncertainty models and coverage objectives; (3) a new guaranteed safe but adaptive paradigm for reactive flight control that is able to generate safety maneuvers even under large disturbances and vehicle dynamics changes, and that can leverage prior flight experience for real-time adaptation; (4) new theory of 3D reconstruction for dynamic scenes captured by UAVs that will enable high-resolution mesh and skeletal reconstruction of the groups of actors. The research outcome will be disseminated through multiple educational activities.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.
虽然已经开发了用于在受控实验室环境中收集数据的大型多摄像机穹顶,但在这种数据收集有很大潜在好处的室外不可能达到类似水平的测量质量。例如,这种测量的使用包括奔跑的猎豹或人的身体动力学,或分析动物或鸟类的放牧行为。这导致科学家依赖于极其低效和危险的数据收集方法。例如,研究野生动物行为的生物学家试图预测动物会出现在哪里,并放置一些摄像头,这些摄像头只在特定位置提供一些有限的数据。该项目通过探索方法的研究和大规模数据收集工具的开发来应对这些挑战,该工具用于使用一组飞行机器人对野外非常大的环境(例如沙漠平原或山坡)中的自然群体行为(例如动物群或人群)进行高分辨率和多视点的视觉记录和运动分析。该项目开发了集成了计算机视觉和多代理控制的基本原理的计算模型,以测量3D中的演员组。通过该系统的开发,该项目将在感知与控制的交叉点技术方面取得重大进展,包括:(1)精确、快速和稳健的目标运动预测和相对状态估计方法的新研究,该方法可以快速估计具有强不确定性估计的机器人和操作者的三维运动;(2)对感知感知的多目标多无人机安全运动规划问题进行新的分解,使得基于一致的操作者预测不确定性模型和覆盖目标的长期规划;(3)新的有保证的安全但自适应的反应式飞行控制范例,即使在大干扰和飞行器动力学变化的情况下也能够产生安全机动,并且可以利用先前的飞行经验进行实时适应;(4)对无人机捕获的动态场景进行三维重建的新理论,将能够对参与者组进行高分辨率网格和骨架重建。研究成果将通过多项教育活动传播。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
3D Human Reconstruction in the Wild with Collaborative Aerial Cameras
- DOI:10.1109/iros51168.2021.9636745
- 发表时间:2021-08
- 期刊:
- 影响因子:0
- 作者:Cherie Ho;Andrew Jong;Harry Freeman;Rohan Rao;Rogerio Bonatti;S. Scherer
- 通讯作者:Cherie Ho;Andrew Jong;Harry Freeman;Rohan Rao;Rogerio Bonatti;S. Scherer
DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion
- DOI:10.1109/cvpr52688.2022.02032
- 发表时间:2021-11
- 期刊:
- 影响因子:0
- 作者:Pei Sun;Jinkun Cao;Yi Jiang;Zehuan Yuan;S. Bai;Kris Kitani;P. Luo
- 通讯作者:Pei Sun;Jinkun Cao;Yi Jiang;Zehuan Yuan;S. Bai;Kris Kitani;P. Luo
Risk-Aware Collision Avoidance for Multi-drone Cinematography
多无人机摄影的风险意识碰撞避免
- DOI:
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Martin, Rebecca and
- 通讯作者:Martin, Rebecca and
Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos
通过观看社交媒体舞蹈视频来学习穿着人类的高保真度深度
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Jafarian, Yasamin and
- 通讯作者:Jafarian, Yasamin and
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Sebastian Scherer其他文献
High-throughput high-resolution cryo-electron crystallography
高通量高分辨率冷冻电子晶体学
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Sebastian Scherer - 通讯作者:
Sebastian Scherer
2dx_automator: implementation of a semiautomatic high-throughput high-resolution cryo-electron crystallography pipeline.
2dx_automator:半自动高通量高分辨率冷冻电子晶体学管道的实现。
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:3
- 作者:
Sebastian Scherer;J. Kowal;M. Chami;V. Dandey;M. Arheit;P. Ringler;H. Stahlberg - 通讯作者:
H. Stahlberg
<em>2dx_automator</em>: Implementation of a semiautomatic high-throughput high-resolution cryo-electron crystallography pipeline
- DOI:
10.1016/j.jsb.2014.03.016 - 发表时间:
2014-05-01 - 期刊:
- 影响因子:
- 作者:
Sebastian Scherer;Julia Kowal;Mohamed Chami;Venkata Dandey;Marcel Arheit;Philippe Ringler;Henning Stahlberg - 通讯作者:
Henning Stahlberg
UniSaT: Unified-Objective Belief Model and Planner to Search for and Track Multiple Objects
UniSaT:统一目标信念模型和规划器,用于搜索和跟踪多个对象
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Leonardo Santos;Brady G. Moon;Sebastian Scherer;Hoa Van Nguyen - 通讯作者:
Hoa Van Nguyen
Planning and Monitoring Multi-Job Type Swarm Search and Service Missions
- DOI:
10.1007/s10846-020-01272-3 - 发表时间:
2021-02-13 - 期刊:
- 影响因子:2.800
- 作者:
Meghan Chandarana;Dana Hughes;Michael Lewis;Katia Sycara;Sebastian Scherer - 通讯作者:
Sebastian Scherer
Sebastian Scherer的其他文献
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