Abstract
The image acquisition system is the main part of acquiring image information, and its performance largely determines the accuracy and difficulty of subsequent planning. The main purpose of this article is to design an image acquisition system for aerobics training based on motion recognition technology. This article mainly introduces the teaching experiments based on the design of aerobics courses. Through the empirical investigation and analysis of the impact of relevant experimental data on aviation training courses, attempts to establish the connection between aerobics social adaptability and various dimensions The cultivation of student’s social adaptability. In this paper, the GMM algorithm is mainly used to distinguish the rest time when the action occurs, and the subsequent rest period is used as the basis for segmenting multiple events in the action sequence. Finally, the characteristics of the action coding mapping of each event are derived, and the support vector machine is used to complete the energy recognition process of the existence of a single energy. The experimental results of this paper show that the designed embedded image acquisition system has high integration and stability, the acquired image resolution is 640x480, and the wireless transmission rate is 5MbPs, which has wide application prospects.
Highlights
In this document, for the held object, the connection point, depth and color information are used to take a color image of the object, identify the type of target, and perform motion recognition in conjunction with the traffic characteristics based on the connection point information
Sequence, and define the static unit between actions according to the action coding diagram
The average recognition rate of the binding data set of action examples is 69.1%, and the average recognition rate of the binding data set of action sequences is 65.1%
Summary
He reports on the effects of training on flexion neuromuscular function. In this document, for the held object, the connection point, depth and color information are used to take a color image of the object, identify the type of target, and perform motion recognition in conjunction with the traffic characteristics based on the connection point information
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