Method for using dynamic trajectory analysis system for exerciser

Abstract

The method for using a dynamic trajectory analysis system for an exerciser uses technologies such as computer vision, edge artificial intelligence (AI), machine learning, and human factors engineering, in conjunction with a smart mobile communication device to perform the following: automatically capturing and recording images of posture of the exerciser during the exercise process; and further analyzing a sport event, sport behavior, and sport equipment in the images, and then obtaining a key information for providing assistance in optimizing the exercise process. The method uses edge AI models to achieve real-time prediction of objective physical performance of objects such as a human body, sport equipment, and a ball in a real environment. A prediction result is presented in a data format and visualized manner, providing a user with a real-time feedback and analysis information.

What is claimed is: 
     
         1 . A method for using a dynamic trajectory analysis system for an exerciser, wherein after an image capturing module of a smart mobile communication device is activated, the smart mobile communication device performs image recording on a physical body of the exerciser to obtain dynamic image data, and performs real-time edge computing, comprising:
 an image recognition operation for performing, by an image recognition module in conjunction with a first model, sport event recognition on content of the dynamic image data and generating a sport event type upon completion of the sport event recognition, performing, by the image recognition module in conjunction with a second model, sport behavior recognition and sport equipment recognition on the dynamic image data to recognize sport behavior and sport equipment in the dynamic image data, and generating raw data upon completion of the sport behavior recognition and the sport equipment recognition, and generating an event to be analyzed by combining the sport event type and the raw data;   a behavioral feature data analysis operation for performing, by an image analysis module in conjunction with a third model, behavioral feature data analysis on the event to be analyzed and generating behavioral feature data; and   a physical performance prediction operation for predicting, by the image analysis module in conjunction with the third model, objective physical performance of a human body, sport equipment, and a ball in a real environment based on the behavioral feature data.   
     
     
         2 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 1 , wherein after the physical performance prediction operation is completed, a reading interface generation operation is subsequently performed, wherein the reading interface generation operation is for generating a reading interface that arranges the behavioral feature data and the objective physical performance in a data format and visualized manner, and is outputted and presented on the smart mobile communication device. 
     
     
         3 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 2 , wherein the reading interface is any one of the following or a combination thereof: a data list, a statistical chart list, or a dashboard-style list. 
     
     
         4 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 1 , wherein after the image recognition operation, a deep analysis operation is performed on the dynamic image data in the event to be analyzed by a deep analysis module of the smart mobile communication device in conjunction with a sports-specific knowledge database, wherein the deep analysis operation is for extracting a key information from the event to be analyzed, and the key information is any one of the following or a combination thereof: an action technique or sport performance. 
     
     
         5 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 4 , wherein through the deep analysis operation in conjunction with a machine vision algorithm, images in the dynamic image data are analyzed, and a precise segment is extracted based on a key movement or moment in the dynamic image data. 
     
     
         6 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 1 , wherein after the image recognition operation, an automatic time sorting operation is performed on segments of the dynamic image data in the event to be analyzed by a time sorting module of the smart mobile communication device, wherein the automatic time sorting operation is for arranging the segments of the dynamic image data in chronological order and generating a training process record. 
     
     
         7 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 1 , wherein a data information in the dynamic image data is presented in an augmented reality (AR) manner by an AR application (APP) installed on the smart mobile communication device, wherein the data information is any one of the following or a combination thereof: a trajectory of a postural change of the exerciser during exercise, a trajectory of ball striking posture, or a trajectory of a moving ball. 
     
     
         8 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 7 , wherein through an AR image, a visual prompt is provided by the AR APP combined with a built-in sensor of the smart mobile communication device to assist in adjusting an angle and a distance of the smart mobile communication device. 
     
     
         9 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 1 , wherein the smart mobile communication device is informationally connected to one or more social platforms to output or publicly share the dynamic image data, a key information, and a data information to the one or more social platforms. 
     
     
         10 . The method for using the dynamic trajectory analysis system for the exerciser of  claim 1 , wherein the smart mobile communication device further collaborates with a remote server and transmits the dynamic image data to the remote server for cloud computing.