用双目相机实现接近激光雷达的室内目标追踪，成本却低十倍以上。
A comparison of extended object tracking with multi-modal sensors in indoor environment
- 结合环境先验信息设计快速启发式检测器，提升追踪效率。
- 双目相机追踪性能接近激光雷达，定位误差差异小于5%。
- 适合低成本智能机器人、巡检设备等场景使用。
本文开展了一项关于室内环境下基于多模态传感器的扩展目标追踪的初步研究，比较了两种不同3D点云传感源——激光雷达与双目相机——的性能表现，二者存在显著价格差异。本研究聚焦于单目标追踪任务，首先开发了一种利用环境与目标先验信息的快速启发式目标检测方法，提取的目标点随后输入到扩展目标追踪框架中，采用星凸超曲面模型对目标形状进行参数化。实验结果表明，使用双目相机的追踪方法性能与激光雷达相当，且成本差异超过十倍。
原文摘要 · Abstract (English)
This paper presents a preliminary study of an efficient object tracking approach, comparing the performance of two different 3D point cloud sensory sources: LiDAR and stereo cameras, which have significant price differences. In this preliminary work, we focus on single object tracking. We first developed a fast heuristic object detector that utilizes prior information about the environment and target. The resulting target points are subsequently fed into an extended object tracking framework, where the target shape is parameterized using a star-convex hypersurface model. Experimental results show that our object tracking method using a stereo camera achieves performance similar to that of a LiDAR sensor, with a cost difference of more than tenfold.
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