Lossless video remote acquisition method and system

Abstract

The invention provides a lossless video remote acquisition method and system, and the method comprises the steps: video information acquisition equipment obtains video information and transmits the video information to a video acquisition module; the video acquisition module receives video information from video information acquisition equipment and transmits the video information to the hardware coding module for compression of video data information; a data cache module receives data from the hardware coding module and the trigger module and then stores video information in a ring and temporary cache region mode; a video data sending module reads the information in the data caching module, transmits the data to the central gateway through the Ethernet, and then continuously sends the data to the vehicle-mounted T-box through the Ethernet, and sends the data to a cloud server. The real-time video stream data is effectively cached, meanwhile, the memory consumption of the system is reduced, the data is stored by using the data slot with the fixed size, and the utilization rate of the memory is greatly improved.

Description

technical field [0001] The invention relates to a lossless video remote acquisition method and system, in particular to the field of data processing. Background technique [0002] With the development of technology, major car companies have begun to apply deep learning and artificial intelligence technology to their own advanced driver assistance systems and autonomous driving products. For example, use the camera to collect the environmental information in front of and around the car, and train the algorithm model of the automatic emergency braking function. [0003] In fact, due to complex road conditions, the trained automatic emergency braking function algorithm model may also cause false triggering of the AEB function due to unpredictable situations, which may also bring potential safety hazards to the driver; at the same time, the existing technology Among them, the algorithm model of artificial intelligence and deep learning depends on a large amount of training data...

AI Technical Summary

Problems solved by technology

[0003] In fact, due to complex road conditions, the trained automatic emergency braking function algorithm model may also cause false triggering of the AEB function due to unpredictable situations, which may also bring potential safety hazards to the driver; at the same time, the existing technology Among them, the algorithm model of artificial intelligence and deep learning depends on a large amount of training data, especially for the video data of the automotive environment, the video after lossy compression and transmission will lose the high-frequency information of the image, and the loss of high-frequency information of the image It will directly affect the effect of deep learning or artificial intelligence model training algorithms; on the other hand, in the face of massive data, storing these video data requires huge storage space and cost

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