A Neural Network Processing Method Based on Self-Assembly Equipment for Optical Image Display Standardization

Liu, Zilong; Jiang, Yiqin; Li, Yuxiao; Li, Jin; Li, Zhuoran; Zhang, Shuguo; Lian, Yusheng; Liu, Ruping

doi:10.1109/access.2019.2942215

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…(1) If N > T, the [T, N] frame was intercepted and discarded, and the [0, T] month frame was used as the normalized bone motion sequence [10] (2) If N < T, the [0, T] frame is used as the normalized bone motion sequence (3) If N = T, [0, T] frame is used as the normalized bone motion sequence without any processing…”

Section: Normalized Skeleton Node Matrixmentioning

confidence: 99%

Research on Tennis Motion Evaluation Method and System Based on Deep Learning

Chang

2022

International Transactions on Electrical Energy Systems

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The current tennis training lacks the guidance to standardize the user action evaluation method; it is difficult to use the human movement analysis related technology to evaluate the user action and feedback. In this paper, a real-time evaluation algorithm for human movements in tennis training with the monocular camera is studied. Aiming at solving the problem of making use of temporal and spatial information of behavior sequence, an improved preprocessing algorithm based on depth image and bone data was proposed, and bone joint feature vectors were constructed to describe the topological shape of the human skeleton. A five-channel convolutional neural network (5C-CNN) model is proposed to effectively train multimodal behavior data. In order to solve the problem of human motion direction, the counterclockwise rotation angle of limbs was proposed as a motion evaluation feature. The experimental test on the MSR Action 3D database shows that the accuracy of the method for tennis movement evaluation reaches 98.1%, which verifies the validity of the model construction.

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Section: Normalized Skeleton Node Matrixmentioning

confidence: 99%

Research on Tennis Motion Evaluation Method and System Based on Deep Learning

Chang

2022

International Transactions on Electrical Energy Systems

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“…These methods influence the uncertainty of grayscale, which is equal to the standardization. Furthermore, the calibration and processing methods of luminance data are also needed for the traceability of grayscale, which we elaborate in another published paper [29].…”

Section: Discussionmentioning

confidence: 99%

A Digital Grayscale Generation Equipment for Image Display Standardization

Jiang

Liu

et al. 2020

Applied Sciences

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The standardization of grayscale display is essentially significant for image signal communication, transmission, and terminal reading. The key step of this standardization is establishing a traceable equipment of grayscale. As a relative value, grayscale is transferred to two different absolute values to satisfy different traceability methods, including optical density for hardcopy image and luminance for softcopy. For luminance, a generation equipment is designed to build the relationship between luminance and grayscale. In this work, novel equipment is established using digital light processing (DLP) by time-frequency modulation, and the corresponding uncertainty is analyzed. The experiment result shows that this digital equipment builds the relationship between grayscale and luminance in the range of 0.16-4000 cd/m2. It enables traceable measurement of grayscale to luminance on this equipment with high accuracy and can provide a standardized reference for the display of grayscale images in the fields of medicine, remote sensing, non-destructive testing, etc.

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