# Dynamic Object Detection in Range data using Spatiotemporal Normals

arXiv: https://arxiv.org/abs/2310.13273 · HTML: https://mlsanity.com/paper/2310.13273/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Oct 2023.

## Built on by (most cited first, 1 of 1)

- [Moving Object Segmentation in Point Cloud Data using Hidden Markov Models](https://mlsanity.com/paper/2410.18638/) (2024)

## Abstract (arXiv)

On the journey to enable robots to interact with the real world where humans, animals, and unpredictable elements are acting as independent agents; it is crucial for robots to have the capability to detect dynamic objects. In this paper, we argue that the detection of dynamic objects can be solved by computing the spatiotemporal normals of a point cloud. In our experiments, we demonstrate that this simple method can be used robustly for LiDAR and depth cameras with performances similar to the state of the art while offering a significantly simpler method.