Lossless video remote acquisition method and system

A technology of remote collection and video, applied in the field of data processing, can solve problems such as hidden safety hazards for drivers, consume huge storage space and cost, and affect the effect of training algorithms, so as to reduce false triggers and improve algorithm models.

Pending Publication Date: 2021-06-01
中汽创智科技有限公司
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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, especial

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  • Lossless video remote acquisition method and system
  • Lossless video remote acquisition method and system
  • Lossless video remote acquisition method and system

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Embodiment Construction

[0053] The invention realizes the purpose of lossless collection of remote video data through a lossless video remote collection method and system. Below through embodiment, in conjunction with accompanying drawing, this scheme is described further in detail.

[0054]The applicant believes that 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 conditions, which may also bring potential safety hazards to the driver. Therefore, in order to improve the model algorithm itself, it is necessary to collect the road environment data before and after the AEB function is falsely triggered, so as to facilitate testing and developers to locate problems, and then import the road environment data into the functional algorithm model for training, improve the algorithm model, and reduce false triggering the occurrence of the situation.

[0055] In the existing technology, o...

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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...

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Application Information

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IPC IPC(8): H04N7/18H04N19/423G07C5/00G07C5/08
CPCH04N7/181H04N19/423G07C5/008G07C5/0866
Inventor 李丰军周剑光
Owner 中汽创智科技有限公司
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