Fusion scale adaptive multi-person pose estimation

Wen Wang; QiongYan Wu; ZhengPeng Zhao; ChenYang Qiu; Yuanyuan Pu; XiaoLong Liu

doi:10.1117/12.2681176

23 May 2023 Fusion scale adaptive multi-person pose estimation

Wen Wang, QiongYan Wu, ZhengPeng Zhao, ChenYang Qiu, Yuanyuan Pu, XiaoLong Liu

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126455I (2023) https://doi.org/10.1117/12.2681176
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Currently, the mainstream top-down multi-person pose estimation algorithms based on convolutional neural networks have achieved high estimation accuracy, but in the standard convolutional neural networks, the perceptual field size of artificial neurons in each layer is designed to be fixed, lacking consideration of the multi-scale problem. To solve this problem, we propose a scale-adaptive multi-person pose estimation method based on the SKNet network introduced in the feature extraction phase of the pose estimation network, which improves the model's ability to extract important features at different scales by weighted fusion of features under different scale branches. DO-Conv is used in the pose estimation network to replace the original two-dimensional convolution, so that it can better capture the important features in the input image, thus further improving the algorithm performance. In addition, a better human detector can improve the performance of the subsequent single person pose estimation network to a certain extent, so the latest YOLOv7 target detector is used in this paper as the human detector in the multi-person pose estimation network. The proposed algorithm is based on the current mainstream multi-person pose estimation algorithms for comparison experiments and shows better performance than the original network itself in the validation experiments on the COCO dataset and the Halpe dataset.

Citation Download Citation

Wen Wang, QiongYan Wu, ZhengPeng Zhao, ChenYang Qiu, Yuanyuan Pu, and XiaoLong Liu "Fusion scale adaptive multi-person pose estimation", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126455I (23 May 2023); https://doi.org/10.1117/12.2681176

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Pose estimation

Convolution

Detection and tracking algorithms

Target detection

Deep learning

Autoregressive models

Performance modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years