CVROFeb 7, 2024

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

arXiv:2402.04953v1h-index: 12
Originality Incremental advance
AI Analysis

This work addresses pose estimation accuracy for computer vision applications, but it appears incremental as it builds on existing models with a filter addition.

The paper tackled pose estimation by adding a Kalman filter to a 4-dimensional deformation part model, resulting in improved accuracy compared to state-of-the-art methods, with the Kalman filter specifically increasing this accuracy.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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