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Application of low light image enhancement algorithm based on pressure sensor fusion in sports training posture analysis
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DOI：10.1007/s13198-026-03228-6.png)
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Abstract
En 中文
In today's information age, it is very important for coaches to do proper sports training and obtain athlete training data. Sports training is composed of various movements, which are composed of continuous human postures. Therefore, this article will design a sports training posture analysis system by using a low light image enhancement algorithm fused with pressure sensors. Firstly, this article analyzes and studies the theoretical foundation of pressure sensors, mainly focusing on the working principle of pressure sensors based on the Wheatstone bridge structure. Secondly, this article also provides a detailed analysis of the relevant research on low light image enhancement, and proposes a low light image enhancement algorithm that can be applied to multiple tasks and scenes, namely the multi-scale Retinex network algorithm. This algorithm can start from the spatial multi-scale representation of images and use various designed network submodules to explore the multi-scale feature information of images at a deeper level. Finally, this article utilizes a low light image enhancement algorithm fused with pressure sensors to design a sports training posture analysis system. This system solves the shortcomings of traditional manual annotation methods and provides more comprehensive and accurate data information for sports training.
Keywords:
Pressure sensor
Low light image enhancement
Sports training
Attitude analysis
Journal
I
IF:
1.4
Papers:
291
Citations:
3.0K