# Real-Time 3D Model Tracking in Color and Depth on a Single CPU Core

arXiv: https://arxiv.org/abs/1911.10249 · HTML: https://mlsanity.com/paper/1911.10249/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Nov 2019.

## Built on by (most cited first, 8 of 8)

- [Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects](https://mlsanity.com/paper/2203.05334/) (2022)
- [SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World](https://mlsanity.com/paper/2110.12715/) (2021)
- [Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review](https://mlsanity.com/paper/2502.14886/) (2025)
- [Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking](https://mlsanity.com/paper/2302.11458/) (2023)
- [Physics-Based Rigid Body Object Tracking and Friction Filtering From RGB-D Videos](https://mlsanity.com/paper/2309.15703/) (2023)
- [Precise Pick-and-Place using Score-Based Diffusion Networks](https://mlsanity.com/paper/2409.09725/) (2024)
- [Robust 6DoF Pose Tracking Considering Contour and Interior Correspondence Uncertainty for AR Assembly Guidance](https://mlsanity.com/paper/2502.11971/) (2025)
- [Robust 6-DoF Object Pose Tracking with Built-In Recovery under Occlusions and Rapid Object Motions](https://mlsanity.com/paper/2607.23468/) (2026)

## Abstract (arXiv)

We present a novel method to track 3D models in color and depth data. To this end, we introduce approximations that accelerate the state-of-the-art in region-based tracking by an order of magnitude while retaining similar accuracy. Furthermore, we show how the method can be made more robust in the presence of depth data and consequently formulate a new joint contour and ICP tracking energy. We present better results than the state-of-the-art while being much faster then most other methods and achieving all of the above on a single CPU core.