Abstract
Background: The effect of teaching and training in physical sports is improved by the sports demonstration system. The two-dimensional sports demonstration system is widely applied for the training of athletes. In accurate motion positioning, there exists a certain visual deficiency and the two-dimensional sports demonstration system is analyzed by kinematics.
Methodology: Aiming at the problems in the real-time tracking of fast-moving targets in sports images, an automatic tracking method of sports images based on the registration of landmark points of the passive optical motion capture system is proposed. Moreover, it aims to build a human model and divide the human model into several limb segments; find the corresponding relationship between the first frame of motion data and template data to complete the first frame of motion data registration; based on the smallest non-rigid deformation and point set matching error, find the corresponding relationship between the current frame of motion data and the previous frame of registered motion data; through the mark points, follow up to complete the registration process of the marker.
Results: Experiments show that the average processing accuracy of this algorithm can reach over 85% and the processing time of a single frame of motion data is t<1/60s, which can meet real-time requirements.
Conclusion: The multi-point set least-squares matching algorithm is used to rigidly correct the registered landmark data. No manual intervention is required for the entire mark registration process.
Keywords: Motion image, real-time tracking, first frame movement, landmark points, sports demonstration, processing accuracy.
Graphical Abstract
Call for Papers in Thematic Issues
Advancements in Brain Tumor Detection and Treatment using Machine Learning, Deep Learning, and Blockchain Technology
Brain tumors are among the most challenging diseases to diagnose and treat, requiring specialized expertise and advanced technology for accurate detection and effective treatment. In recent years, machine learning and deep learning algorithms have shown promise in improving the accuracy and efficiency of brain tumor detection through medical imaging analysis. ...read more
Advances of Biometric Data Analysis to Boost Intelligent Applications
With the rapid development of artificial intelligence (AI) technology, more and more intelligent devices and applications are appearing in our daily lives, such as smart home, smart agriculture, health diagnosis, educational support, and environmental monitoring. Interaction with these devices or applications has become a pressing issue that can greatly improve ...read more
Attainment of SDGs through the Advancement in Solar Energy Systems
With less than a decade until we reach 2030, it is crucial to address the deep inequalities affecting not only our health but also our quality of life, and the economy of countries worldwide. Few of the UN's Sustainable Development Goals (SDGs) can be directly and indirectly achieved through the ...read more
Emerging Intelligent Computing Techniques and their Applications Using Machine Learning
This special issue will aim to discuss computational intelligence approaches, initiatives and applications in engineering and science fields (including Machine Intelligence, Mining Engineering, Modeling and Simulation, Computer, Communication, Networking and Information Engineering, Systems Engineering, Innovative Computing Systems, Adaptive Technologies for Sustainable Growth, and Theoretical and Applied Sciences). This collection should ...read more
Related Journals
Recent Patents on Engineering
7