2 Work principle

NVRs receive a stream from video cameras. An encoded video stream or reference frames of this video stream are sent to the computing server, depending on the detector. After that, processing and analytics take place, then the results are returned to the source server.

For offload detectors, video analytics works as follows:

1. The data is sent to the machine;
2. Operations related to neural networks and/or using GPUs are transferred to a remote machine with suitable hardware;
3. The results of the detector operation are returned to the data source machine.

This makes it possible to efficiently use the available hardware resources.

That is, in fact, offload video analytics is remote video analytics: the ability to transfer calculations to another server.

2.1 Example

Let's say there are already several cameras connected to MiniNVR video recorders, the image from which we can view in the TRASSIR Client. We want to connect a neural network queue detector.  However, the MiniNVR series recorders do not support local neuro analytics. But you can connect a NVR from the NeuroStation series to MiniNVR, and transfer the video stream from MiniNVR to it.  If necessary, you can connect the cameras directly to the NVR with analytics.

After analyzing the video, the analytics server returns the data with detections to the source server from which the offload was performed. Thus, we can use the results of neural network analytics, regardless of the fact that the video stream is recorded on the MiniNVR recorder, which is simple in functionality.