The application of big data in the field is mainly reflected in two aspects: video recording cluster and video structured data query and information mining.
1. Cluster storage of video recording
In the big data-oriented architecture, one or more clusters can be set up according to the actual site deployment needs. The collected streaming data will be divided into segments and distributed among the data cluster nodes, because the cluster nodes have internal multiple copy backups For other mechanisms, software technology can ensure the high reliability and stability of the overall system. These data nodes can use cheap general-purpose hardware, avoid the traditional high-end hardware model, and can greatly reduce investment costs.
For cluster storage of video files, domestic cloud storage manufacturers mostly adopt the methods of CEPH technology and HDFS technology. Taking HDFS as an example, the idea is: through the API structure provided by HADOOP, the received video stream file can be uploaded from the local to HDFS. In this process, the received video files are continuously stored in a designated local temporary folder, and this local folder is constantly changing dynamically, you can use this folder as a "buffer", The files in the "buffer" will be uploaded to HDFS in a streaming manner.
2. Video structured data query and information mining
The original video image is a kind of unstructured data, which cannot be directly read and recognized by the computer and the upper application software. In order to make the video image better applied, the video image must be structured and extracted to extract key information , And the semantic description of the text, which is the structure of the video.
In a video, there are two main types of key information that need to be extracted: the first type is the recognition of moving objects, that is, the recognition of moving objects in the picture, whether it is a person or a motor vehicle or a non-motor vehicle; the second type is the characteristics of moving objects Recognition, that is, what are the characteristics of people, cars, and objects moving in the picture? The main characteristics of pedestrians are: whether they wear glasses, scarves, tops, pants, whether they wear masks, whether they are backpacks, gender classification, etc .; the main characteristics of motor vehicles are: license plates Number, body color, model, etc .; the main features of the object are: size, color, direction, etc.
The review of a case requires more extensive viewing of relevant camera video, and the amount of video viewed often reaches hundreds or thousands of hours. Video structured extraction technology extracts moving objects in the video, and then retrieves and excludes through the software, which can greatly improve the efficiency of handling cases.
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