Design of car audio and video synchronization algorithm based on neural network model

Bin Li; Haipeng Cao

doi:10.1117/12.2688736

11 September 2023 Design of car audio and video synchronization algorithm based on neural network model

Bin Li, Haipeng Cao

Author Affiliations +

Proceedings Volume 12779, Seventh International Conference on Mechatronics and Intelligent Robotics (ICMIR 2023); 127791E (2023) https://doi.org/10.1117/12.2688736
Event: Seventh International Conference on Mechatronics and Intelligent Robotics (ICMIR 2023), 2023, Kunming, China

Abstract

The transmission process of automobile monitoring video network will be disturbed by complex network environment, such as network delay, jitter and other factors, which will lead to the phenomenon of multimedia asynchronization, and audio-video synchronization, as one of the key technologies, has attracted more and more attention. In this paper, an audio-video synchronization algorithm of automobile monitoring video based on neural network model is proposed. By improving the variable-length coding algorithm and its mapping rules, the audio information is dynamically grouped, and the dynamic double mapping relationship between prediction mode group and variable-length code group is established. The simulation results show that the algorithm can ensure the correctness and integrity of audio data, and realize the synchronous coding transmission of high-definition and ultra-high-definition video. The algorithm is applied to vehicle monitoring video, which ensures the time constraint relationship between audio data and video data, that is, realizes the synchronous playback of audio and video, thus effectively ensuring the driver's driving safety, avoiding traffic accidents and making it easier for the driver to drive the vehicle.

Citation Download Citation

Bin Li and Haipeng Cao "Design of car audio and video synchronization algorithm based on neural network model", Proc. SPIE 12779, Seventh International Conference on Mechatronics and Intelligent Robotics (ICMIR 2023), 127791E (11 September 2023); https://doi.org/10.1117/12.2688736

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