A comparison of extended object tracking with multi-modal sensors in indoor environment

TL;DR

This study compares the effectiveness of LiDAR and stereo camera sensors for single object tracking in indoor environments, demonstrating that stereo cameras can achieve similar performance to LiDAR at a significantly lower cost.

Contribution

The paper introduces a fast heuristic object detector and an extended object tracking framework that works effectively with stereo camera data, offering a cost-efficient alternative to LiDAR.

Findings

Stereo camera tracking performance comparable to LiDAR

Cost difference exceeds tenfold between sensors

Effective single object tracking in indoor environments

Abstract

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.