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

arXiv 2402.04953 ↗First posted 7 Feb 2024cs.CV cs.ROcited by 0

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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.

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

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References · 2

  1. 2013DeepPose: Human Pose Estimation via Deep Neural Networkscited by 305
  2. 2013Beyond Physical Connections: Tree Models in Human Pose Estimationcited by 14

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