Dance somersault gesture recognition based on multi-scale depth feature fusion

Lusi Huang

doi:10.1117/12.2671568

16 March 2023 Dance somersault gesture recognition based on multi-scale depth feature fusion

Lusi Huang

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 1259314 (2023) https://doi.org/10.1117/12.2671568
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

In order to explore the problem of dance somersault gesture recognition, a kind of dance somersault gesture recognition based on multi-scale depth feature fusion is proposed. Methods Through the information recommendation of key technical problems and solutions based on multi-scale depth feature fusion, the research of dance somersault gesture recognition was explored. The research shows that the efficiency of dance somersault gesture recognition based on multi-scale depth feature fusion is about 4.6% higher than that of traditional methods. The acquisition of main video information has always been inclined to obtain video key frames. However, in the face of videos with strong continuity and low repetition between human posture sequences in various movements, only key frames can't represent all the effective information of the videos. Most algorithms excessively pursue the differences between action categories, thus ignoring the degree of "cohesion" between simple actions within actions.

Citation Download Citation

Lusi Huang "Dance somersault gesture recognition based on multi-scale depth feature fusion", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 1259314 (16 March 2023); https://doi.org/10.1117/12.2671568

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KEYWORDS

Video

Gesture recognition

Video surveillance

Feature fusion

Video processing

Motion analysis

Motion detection

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