# 4-Dimensional deformation part model for pose estimation using Kalman filter constraints

arXiv: https://arxiv.org/abs/2402.04953 · HTML: https://mlsanity.com/paper/2402.04953/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 35 references that are in the map.
- First posted on arXiv 7 Feb 2024.

## Builds on (most cited first, 2 of 2)

- [DeepPose: Human Pose Estimation via Deep Neural Networks](https://mlsanity.com/paper/1312.4659/) (2013)
- [Beyond Physical Connections: Tree Models in Human Pose Estimation](https://mlsanity.com/paper/1305.2269/) (2013)

## Abstract (arXiv)

The main goal of this article is to analyze the effect on pose estimation accuracy when using a Kalman filter added to 4-dimensional deformation part model partial solutions. The experiments run with two data sets showing that this method improves pose estimation accuracy compared with state-of-the-art methods and that a Kalman filter helps to increase this accuracy.