Research on sports video detection technology motion 3D reconstruction based on hidden Markov model
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Research on sports video detection technology motion 3D reconstruction based on hidden Markov model Yao Lu1 • Shuyang An1 Received: 13 September 2019 / Revised: 13 September 2019 / Accepted: 19 March 2020 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The difficulty of sports video detection technology lies in how to detect the end point segment from the complex video speech environment, and the artificial intelligence technology is still in the research stage. Based on this, this study builds a model based on the hidden Markov model. At the same time, the video file noise reduction processing is performed by the spectral subtraction noise reduction algorithm of the complex domain extension. Moreover, combined with the actual situation of sports competitions, this paper proposes an endpoint detection algorithm based on variance characteristics, and comprehensively designs a speech recognition model based on Markov model. In order to verify the validity of the model, the performance of the model is verified by an example, and the real sports competition is taken as the research object, and the accuracy rate and the recall rate are set as performance indicators. The research shows that the model proposed in this study performs well in both accuracy and performance rate and can be used as a reference for artificial intelligence application to sports video detection technology. Keywords Hidden markov model Sports video Voice Detection
1 Introduction The research of content-based sports video analysis methods has become a key branch of video semantics, and it has received a lot of attention in both academic and commercial aspects. The reason is that it has great commercial value, and also involves many fields of signal processing, artificial intelligence, computer vision, pattern recognition, human–computer interaction, database, etc., which has important theoretical significance [1]. The core technology of sports video analysis is actually to detect the target event by extracting specific features and create a summary with the target event as the content. The research based on video analysis of sports games mainly has the following characteristics [2]: (1) There are many sports competitions, including football, billiards, rugby, figure skating, etc. (2) Sports videos, especially football, tennis, basketball and other game videos have a longer duration, while the really & Shuyang An [email protected] 1
Physical Education Department, Shanghai University of Finance and Economics, Shanghai 200433, China
exciting clips only account for a small part, and the video is more redundant. In the early 1990s, the concept of semantics was introduced into the field of video processing. The method is mainly to fully consider the human emotion information expressed by the video object, so that the video can be processed by the computer more realistically in the way that the human cognition of the video semantic content. Therefore, this method aims to s
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