Documentation for Axxonsoft Platform Calculator. Documentation for other products available here.

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The following detection tools are available for Intellect and vertical solutions platform calculation:

Name

DescriptionFeatures of calculation
IntLab-Carriages (passenger)Recognizer of railway passenger carriage numbers
  1. Optimal resolution of 704*288 OR 640*360 and fps = 25. At a higher resolution the module will not be able to process all frames reducing quality of operation.
  2. Main channel has the same resources consumption as subordinate channel.
IntLab-Carriages (freight)Recognizer of railway freight carriage numbers
  1. Optimal resolution of 704*288 OR 640*360 and fps = 25. At a higher resolution the module will not be able to process all frames reducing quality of operation.
  2. Main channel has the same resources consumption as subordinate channel.
Video Content Analytic

Object trajectories detection tool.

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Face detection (Cognitec)

Face-Intellect face detection tool based on the Cognitec recognition module.

When calculating a platform using this detection tool, only resources for faces detecting and vectorization are taken into account. The load from comparing faces with a reference database is not taken into account, because usually a separate server is provided to perform this function.
Face Detection (Huawei)

Face-Intellect face detection tool based on the Huawei recognition module.

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Face detection (STC)Face-Intellect face detection tool based on the STC recognition module.
Face detection (TVN)

Face-Intellect face detection tool based on the Tevian recognition module.

When calculating a platform using this detection tool, only resources for faces detecting and vectorization are taken into account. The load from comparing faces with a reference database is not taken into account, because usually a separate server is provided to perform this function.
Main motion detectionBasic motion detection tool in Intellect (a detection that is turned on when camera is armed)-

LPR VT

Auto-Intellect, VIT license plate recognition module.

-

People Counter

People counter detection tool that is a part of Intellect Detector Pack.

Optimal parameters for this detection tool are resolution of 800x600 / 640x360 / 640x480 / 320x240 and FPS of 24 to 30. If  specified parameters of the video stream do not meet these conditions, then when you select this detection tool the resolution is set to 320x240 and FPS to 24.

Virtual Loop

Auto-Intellect, Vehicle detector module and Vehicle processor module that are the part of the information-gathering subsystem.

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Virtual Loop (IV)Auto-Intellect, IntelliVision Traffic Monitoring Module that is the part of the information-gathering subsystem.-
Glow detectionDetection of light sources status on the video that is a part of Intellect Detector Pack.-
Heat Map DetectionHeat map detection tool that is a part of Intellect Detector Pack.-
Fire and smoke Detection (CPU)Fire and smoke detection based on neural networkIn order to enhance quality of operation and reduce CPU usage, it is recommended to use the detection tool with calculation on GPU.
Fire and Smoke Detection (GPU)Fire and smoke detection based on neural network using the GPU resources

500 MB of video memory per detection type is required regardless of the number of channels. For example, for any number of smoke detection channels, 500 MB is required, and if the server has any number of both smoke and fire detector channels at the same time, a video card with at least 1 GB of memory should be in use.

Several video cards can be in use in one system.

If the Time in seconds between processed frames parameter is set to the default value (10 seconds), any NVidia graphics card compatible with the detection tool will be suitable (see the requirements in the documentation for the Detector Pack subsystem).

VCA with neural filter (GPU)

Object trajectories detection tool (VMDA) based on neural network and using the GPU resources

For each track, one image per second is sent to neural network for classification.

  • The NVIDIA GeForce GT 730 video card is capable of processing about 70* classifications** per second.
  • The NVIDIA GeForce GTX 1070 video card is capable of processing about 220*** classifications per second.
  • The NVIDIA Tesla P40 video card is capable of processing about 122**** classifications per second.
  • The Intel Neural Compute Stick 1 (movidius I) is capable of processing about 58***** classifications per second.

  • The Intel Neural Compute Stick 2 (movidius II) is capable of processing about 200***** classifications per second.

Several video cards can be in use in one system.

For example, if you need to track 9 persons per second on 10 cameras, GeForce GTX 1070 or similar video card is suitable.

Up to two Intel Neural Compute Stick can be in use in one system.

LPR IVAuto-Intellect, IntelliVision license plate recognition module.-
Service detection

Intellect detection tools:

  • focusing detection tool;
  • video signal stability detection tool;
  • background change detection tool;
  • camera blinding detection tool;
  • camera covering detection tool.
The platform is calculated for one service detection tool (any of the listed)
VCA (Axis ACAP)For Axis IP-devices only. This is an AxxonSoft Video Content Analytic (VCA) detection tool built into Axis device. See also AxxonSoft tracking in Axis devices (Intellect) or AxxonSoft tracking in Axis devices (Axxon Next).The detection tool performs calculations using camera resources, and therefore has low hardware requirement
Neural tracker (CPU, 6fps)Neural tracker that is a part of Detector Pack subsystemThe frame rate shown in parentheses is specified when configuring the Neurotracker module (with the Frame rate limit parameter). This is the number of frames per second processed by the module; the frame rate of the incoming video stream is usually higher.

Note.

* - The results are given for Core i5-3570 (3400 MHz) CPU and may vary depending on the CPU installed. For example, the Xeon Gold 6140 (2300 MHz) CPU allows 95 classifications** per second.

** -1 classification per second is 1 object detected on video. For example, if average of 9 moving objects are simultaneously present on video from one camera, and there are 5 cameras in the system, use video card allowing 45 classifications per second.

*** - The results are given for the Core i7-8700 (3200 MHz) CPU and may vary depending on the CPU installed.

**** - 360 classifications per second were achieved in test utility on the 2x Intel Xeon Gold 6140 platform. In Axxon Next, up to 122 classifications per second were possible with 90% CPU utilization.

***** - The results are given for the Core i7-3770 (3400 MHz) CPU and may vary depending on the CPU installed.

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