Comparison of action recognition from video and IMUs

Podoprosvetov, Aleksei Valerievich; Alisejchik, A.P.; Orlov, Igor

doi:10.1016/j.procs.2021.04.144

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…It can also be understood as the distribution of the same feature in different groups of data and in different time periods. Using HMM to recognize human behavior mainly involves the following three processes [10].…”

Section: Image Extractionmentioning

confidence: 99%

Sports Teaching Action Recognition Based on Hybrid CNN-HMM

Xie,

Ding

2024

Advances in Transdisciplinary Engineering

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In order to automatically recognize abnormal actions in physical education teaching in intelligent monitoring system, a CNN and HMM based action recognition model is proposed. In this scheme, the camera and computer are used to capture and measure the target, and the preliminary features of the image acquired from the data are extracted. Then, hybrid CNN-HMM is introduced as the key technology and main method of behavior recognition, and principal component analysis is also used to reduce the dimension of the extracted feature parameters. Finally, the test set is input into the trained classifier for action recognition, which provides an auxiliary reference for teaching actions. The experimental results show that the system can accurately quantify the human movements in sports teaching, and the recognition accuracy of complex databases with different scenes is better than that of similar methods.

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Section: Image Extractionmentioning

confidence: 99%

Sports Teaching Action Recognition Based on Hybrid CNN-HMM

Xie,

Ding

2024

Advances in Transdisciplinary Engineering

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“…A dance-aided training system based on posture recognition is developed, which combines dance training with posture recognition, human bone recognition, and tracking technology to recognize posture. Data processing and data analysis are the main components of this system [23][24][25]. e collected data include the movement data of dance coaches and the movement data of trainers.…”

Section: Implementation Of Sports Dance Movement Detectionmentioning

confidence: 99%

Research on Sports Dance Movement Detection Based on Pose Recognition

Tang

Hyun-Joo

2022

Mathematical Problems in Engineering

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In view of the poor effect of current sports dance movement detection, this paper puts forward a sports dance movement detection method based on posture recognition. By using the principle of posture recognition to obtain the characteristic information of sports dance movement, construct the action characteristic evaluation system, optimize the action detection algorithm combined with posture recognition technology, and realize the classified detection of sports dance movements. Finally, experiments show that the sports dance movement detection based on pose recognition has high practicability and effectiveness in the process of practical application and fully meets the research requirements.

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Human motion recognition based on Nano-CMOS Image sensor

Li¹,

Liu²

2023

MBE

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<abstract> <p>Human motion recognition is of great value in the fields of intelligent monitoring systems, driver assistance system, advanced human-computer interaction, human motion analysis, image and video processing. However, the current human motion recognition methods have the problem of poor recognition effect. Therefore, we propose a human motion recognition method based on Nano complementary metal oxide semiconductor (CMOS) image sensor. First, using the Nano-CMOS image sensor to transform and process the human motion image, and combines the background mixed model of pixels in the human motion image to extract the human motion features, and feature selection is conducted. Second, according to the three-dimensional scanning features of Nano-CMOS image sensor, the human joint coordinate information data is collected, the state variables of human motion are sensed by the sensor, and the human motion model is constructed according to the measurement matrix of human motions. Finally, the foreground features of human motion images are obtained by calculating the feature parameters of each motion gesture. According to the posterior conditional probability of human motion images, the recognition objective function of human motion is obtained to realize human motion recognition. The results show that the human motion recognition effect of the proposed method is good, the extraction accuracy is high, the average human motion recognition rate is 92%, the classification accuracy is high, and the recognition speed is up to 186 frames/s.</p> </abstract>

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Comparison of action recognition from video and IMUs

Cited by 3 publications

References 4 publications

Sports Teaching Action Recognition Based on Hybrid CNN-HMM

Sports Teaching Action Recognition Based on Hybrid CNN-HMM

Research on Sports Dance Movement Detection Based on Pose Recognition

Human motion recognition based on Nano-CMOS Image sensor

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