Optical super-resolution imaging based on improved planning algorithm in sports teaching simulation

Wei, Wei; Lu, Liu

doi:10.1007/s11082-023-06009-8

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…These methods often rely on static image processing techniques and struggle to effectively handle image degradation issues caused by motion blur and camera shake [13][14][15]. Moreover, traditional algorithms usually have high computational demands and poor real-time performance when dealing with high-dynamic scenes, which are not suitable for sports event analysis that requires quick feedback [16][17][18][19][20][21]. Therefore, developing super-resolution techniques optimized for motion scenarios has become an important research direction in this field.…”

Section: Introductionmentioning

confidence: 99%

Image Super-Resolution Reconstruction in Sports Scenarios and Its Application in Motion Analysis

2024

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With the rapid development of sports technology, the demand for high-definition images in sports competition analysis has been increasing. Particularly in fast-paced sports such as basketball, traditional image capture technology often fails to provide sufficient detail resolution, limiting in-depth analysis of athletic techniques and tactical layouts. To address this, image super-resolution reconstruction technology has been extensively studied and applied to enhance image quality, thereby providing coaches and analysts with clearer visual materials. However, existing super-resolution methods mainly focus on static images and struggle to overcome the challenges of blurring and real-time processing demands in motion scenarios. This paper introduces a dynamic adaptive cascaded network-based method for super-resolution reconstruction of images in motion scenarios, combined with dynamic 3D motion scene imaging techniques, aimed at enhancing the accuracy and timeliness of motion analysis. Through these innovative methods, not only can image degradation caused by motion be effectively handled, but higher-dimensional data support can also be provided for motion analysis.

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Section: Introductionmentioning

confidence: 99%

Image Super-Resolution Reconstruction in Sports Scenarios and Its Application in Motion Analysis

2024

View full text Add to dashboard Cite

show abstract

Optical super-resolution imaging based on improved planning algorithm in sports teaching simulation

Cited by 1 publication

References 13 publications

Image Super-Resolution Reconstruction in Sports Scenarios and Its Application in Motion Analysis

Image Super-Resolution Reconstruction in Sports Scenarios and Its Application in Motion Analysis

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