概括
本研究介绍了基于事件的结构光 (SL) 系统的循环空间编码策略. 这种新的方法提高了深度感应的准确性和效率,使得高速的3D重建成为可能.
科学领域:
- 机器人和计算机视觉 机器人和计算机视觉
- 神经形态工程的神经形态工程
背景情况:
- 基于事件的结构光 (SL) 系统使用事件摄像头提供高速,高动态范围和低功率的深度传感.
- 目前基于事件的SL中的空间编码方法在扫描速度和重建质量之间存在权衡.
研究的目的:
- 为基于事件的SL系统开发一种新的循环空间编码策略.
- 为了提高深度重建的准确性,同时保持基于事件的SL的高效率.
主要方法:
- 设计了一个循环空间编码策略,通过对的斑点位移嵌入几何约束.
- 为了利用这些限制,开发了一个几何先导立体匹配算法.
- 建议采用多框架增强策略,以提高活动框架质量.
主要成果:
- 提出的循环空间编码策略有效地提高了基于事件的SL系统的性能.
- 高精度的深度重建是通过利用嵌入式几何约束来实现的.
- 该系统在1000 FPS的高率下展示了强大的3D传感能力.
结论:
- 新的循环空间编码策略和相关算法显著提升了基于事件的结构光系统.
- 这种方法为高精度,高速3D传感应用提供了有前途的解决方案.
- 该方法在具有挑战性的动态场景中为立体匹配和深度重建提供了坚实的基础.
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