A spatio-temporal-frequency features fusing based lightweight human pose estimation network

Yuechao Sun; Dehui Kong; Jinghua Li; Baocai Yin

doi:10.1117/12.3019904

25 March 2024 A spatio-temporal-frequency features fusing based lightweight human pose estimation network

Yuechao Sun, Dehui Kong, Jinghua Li, Baocai Yin

Proceedings Volume 13089, Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023); 1308919 (2024) https://doi.org/10.1117/12.3019904
Event: Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023), 2023, Suzhou, China

Abstract

Capturing the hidden relationships in 2D pose sequences is crucial for accurate 3D human pose estimation(HPE). Recent studies have shown that frequency domain information, independent of spatio-temporal information, has strong capabilities on representing the pose sequences. However, there are few works exploring more appropriate ways to fuse these different kinds of information. In this paper, we propose an alternating cyclic approach for fusing spatio-temporal information and frequency information to achieve accurate 3D human pose estimation. The designed alternating cyclic fusion network allows for a more comprehensive integration of different features, leading to improved accuracy. By leveraging feature splitting and time-frequency convolution, the existing features are processed more appropriately, and achieving model lightweighting. Experimental results demonstrate that our approach achieves comparable accuracy to state-of-the-art methods while significantly outperforming mainstream methods in terms of model lightweighting. In conclusion, the introduction of frequency domain information is of great significance for pose estimation tasks.

Citation Download Citation

Yuechao Sun, Dehui Kong, Jinghua Li, and Baocai Yin "A spatio-temporal-frequency features fusing based lightweight human pose estimation network", Proc. SPIE 13089, Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023), 1308919 (25 March 2024); https://doi.org/10.1117/12.3019904

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