Exploiting AdaRank Model and Trajectory of Hand Motion for Hand Gesture Recognition

Fahn, Chin-Shyurng; Kao, Chang-Yi; Yao, Ching-Bang; Wu, Meng-Luen

doi:10.1166/sl.2016.3743

Cited by 4 publications

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“…Experimental results show that Fahn et al's method has high performance and can run in real time. For practical applications, the accuracy of this method is also very high [26]. The energy expenditure of the human arm is important for seeking the optimal human arm trajectory.…”

Section: Introductionmentioning

confidence: 99%

Optimal Recognition of Volleyball Player’s Arm Movement Track Based on Embedded Microprocessor

Liu

Tao

2022

Wireless Communications and Mobile Computing

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An embedded microprocessor is the core part of the integrated circuit system, and it represents one of the highest levels of a digital integrated circuit design. Therefore, the design of low-power embedded microprocessors has become an important research direction in the integrated circuit design. Volleyball has always been a very important sport in our country, and it is a sport that the masses of people like to see. The basic techniques of volleyball include ready posture and movement, serving, hot ball, passing, smashing, and netting. The research content of this article is a simulation study of volleyball players’ arm trajectory optimization recognition. In response to the above problems, this paper proposes an optimized recognition method based on the volleyball player’s arm motion trajectory. The simulation results show that the method has high recognition accuracy and provides a strong scientific basis for improving the volleyball players’ spike skills. Without interference from the right arm, the controller input and position tracking error will not fluctuate in 1 ≤ T ≤ 3 , the controller input is stable, and the output error is zero. Based on the above simulation analysis, it can be seen that the control method does not require the robot kinematics and dynamics model to generate any regression matrix when designing the controller. The controller is suitable for the performance tracking of humanoid robot arms.

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Section: Introductionmentioning

confidence: 99%

Optimal Recognition of Volleyball Player’s Arm Movement Track Based on Embedded Microprocessor

Liu

Tao

2022

Wireless Communications and Mobile Computing

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Network education recommendation and teaching resource sharing based on improved neural network

Yuan

2020

IFS

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Intelligent network teaching system provides learners with abundant teaching resources and convenient, excellent and efficient learning environment. However, network teaching resources are widely distributed and difficult to centralize. Resource sharing has become a key problem to be solved in the network environment. The current research on online education resource recommendation mainly focuses on offline education, and there are few studies on online education resources. Based on this, this study studies the link prediction methods in online education and establishes appropriate models for online education. In the research, through improved analysis of traditional algorithms, an improved neural network path sorting algorithm based on path sorting method is proposed. At the same time, we use the path sorting algorithm based on random walk model and neural network-path sorting algorithm to realize the link prediction problem in the online learning knowledge base. In addition, the performance analysis of the algorithm is carried out by contrast method, and the performance comparison analysis is carried out by combining various common traditional recommendation algorithms with the research algorithm of this study.

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Research on basketball players’ action recognition based on interactive system and machine learning

Jin

2021

IFS

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The difficulty of sports gesture recognition is the effective cooperation of hardware and software. Moreover, there are few studies on machine learning in the capture of the details of sports athletes’ gesture recognition. Therefore, based on the learning technology, this study uses the sensor with gesture recognition algorithm to analyze the detailed motion capture of sports athletes. At the same time, this study selects inertial sensor technology as the gesture recognition hardware through comparative analysis. In addition, by analyzing the actual needs of athletes’ gesture recognition, the Kalman filter algorithm is used to solve the athlete’s posture, construct a virtual human body model, and perform sub-regional processing, so as to facilitate the effective identification of different limbs. Finally, in order to verify the validity of the algorithm model, the basketball exercise is taken as an example for experimental analysis. The research results show that the basketball gesture recognition method used in this paper is quite satisfactory.

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Exploiting AdaRank Model and Trajectory of Hand Motion for Hand Gesture Recognition

Cited by 4 publications

References 0 publications

Optimal Recognition of Volleyball Player’s Arm Movement Track Based on Embedded Microprocessor

Optimal Recognition of Volleyball Player’s Arm Movement Track Based on Embedded Microprocessor

Network education recommendation and teaching resource sharing based on improved neural network

Research on basketball players’ action recognition based on interactive system and machine learning

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