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EC-WAMI:以事件摄像机为基础的姿势优化在遥感和广域运动图像中

Isaac Nkrumah¹, Maryam Moshrefizadeh¹, Omar Tahri²

¹Artificial Intelligence and Robotics Lab (AIRLab), Department of Computer Science, Saint Louis University, Saint Louis, MO 63103, USA.

Sensors (Basel, Switzerland)

|December 17, 2024

概括

神经形态事件摄像头 (ECs) 通过检测照明变化,从广域运动图像 (WAMI) 实现准确的3D重建. 这项技术为遥感和空中成像应用提供了优势.

科学领域:

计算机视觉计算机视觉
机器人技术机器人技术机器人技术
遥感遥感遥感遥感

背景情况:

传统的基于的摄像机在空中成像方面面临着挑战,原因是照明变化和功率限制.
神经形态事件摄像头 (ECs) 通过检测像素级亮度变化,提供高时间分辨率,低功耗和对动态照明的弹性.

研究的目的:

为广域运动图像 (WAMI) 和遥感 (RS) 提供EC的首个应用程序.
评估EC在各种成像场景中的结构从运动 (SfM) 和3D重建的潜力.
评估EC在摄像头姿势恢复和为WAMI生成3D点云方面的有效性.

主要方法:

从RGB WAMI图像中模拟事件数据.
将模拟的EC数据集成到最先进的SfM管道 (COLMAP和顺序图像捆绑调整 - BA4S).
评估特征提取方法,包括基于深度学习的LIGHTGLUE描述符.

主要成果:

在WAMI场景中,EC可以实现精确的摄像头姿势恢复,即使是在低率 (5fps) 的模拟中.
BA4S的准确性相当于COLMAP的准确性,但在速度方面表现明显优于它.
与基于事件的SfM的传统手工描述器相比,LIGHTGLUE描述器显示出更高的可靠性和准确性.

结论:

事件摄像头 (EC) 对于从运动结构 (SfM) 和在广域运动图像 (WAMI) 和遥感 (RS) 中的3D重建是有效的.
在具有挑战性的照明条件下,EC克服了传统传感器的局限性,并延长了无人机的耐用性.
这些发现突出了ECs在先进的空中成像和3D重建应用中的广泛潜力.

关键词:

瓦米的瓦米是个非常好的城市.捆绑调整的调整.事件摄像机事件摄像机功能提取特性提取构成了优化优化.远程传感是一种遥感技术.结构来自运动的结构.

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