Future Pose Prediction from 3D Human Skeleton Sequence with Surrounding Situation

Author:

Fujita TomohiroORCID,Kawanishi YasutomoORCID

Abstract

Human pose prediction is vital for robot applications such as human–robot interaction and autonomous control of robots. Recent prediction methods often use deep learning and are based on a 3D human skeleton sequence to predict future poses. Even if the starting motions of 3D human skeleton sequences are very similar, their future poses will have variety. It makes it difficult to predict future poses only from a given human skeleton sequence. Meanwhile, when carefully observing human motions, we can find that human motions are often affected by objects or other people around the target person. We consider that the presence of surrounding objects is an important clue for the prediction. This paper proposes a method for predicting the future skeleton sequence by incorporating the surrounding situation into the prediction model. The proposed method uses a feature of an image around the target person as the surrounding information. We confirmed the performance improvement of the proposed method through evaluations on publicly available datasets. As a result, the prediction accuracy was improved for object-related and human-related motions.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. PepperPose: Full-Body Pose Estimation with a Companion Robot;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

2. ACTION RECOGNITION OF SIMULATED WORKPLACE WITH OCCLUSION BASED ON INTERPOLATED SKELETON DATA USING OPENPOSE;INT J INNOV COMPUT I;2024

3. A Dual Perspective of Human Motion Analysis - 3D Pose Estimation and 2D Trajectory Prediction;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

4. Computer Vision in Human Analysis: From Face and Body to Clothes;Sensors;2023-06-06

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