Documentation for Axxonsoft Platform Calculator. Documentation for other products available here.
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The following detection tools are available for Axxon Next platform calculation:
Name | Description | Features of calculation |
| Video Content Analytic | Object trajectories detection tool. | - |
Motion Detection | NOT a smart video detection tool (Motion detection). | - |
Motion Detection (decode key frames) | NOT a smart video detection tool (Motion detection) with key frames decoding enabled. | - |
| License Plate Recognition | License plate recognition detection tool | - |
| Face Search | Face search detection tool | - |
| Fire and smoke Detection (CPU) | Fire and smoke detection based on neural network | In 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 between processed frames in seconds 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 Axxon Next User Guide). |
| Pose detection (CPU, 3fps) | Pose detection based on neural network | The number of specific pose detection tools created under the Pose detection object does not affect the calculation results (except Close-standing people detection which contributes to the overall load). The platform is calculated for Delay between two measurements value of 333 ms (i.e. 3 fps which is different from the default value). |
| 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.
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. |
| Video Content Analytics (IV) | A smart video detection tool | - |
| Service detection (key frames) | Axxon Next detection tools:
| 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 requirements. |
| Neural tracker (CPU, 6fps) | Scene Analytics tool based on neural tracking | The frame rate shown in parentheses is specified when configuring the Neurotracker module (with the Frame rate parameter). This is the number of frames per second processed by the module******; the frame rate of the incoming video stream is usually higher. |
| Neural tracker (VPU, 6fps) | Scene Analytics tool based on neural tracking using the Vision processing unit (VPU) resources | 1 x Mustang-V100-MX8 (Intel HDDL) card processes up to 60****** video channels regardless of video resolution. The frame rate shown in parentheses is specified when configuring the Neurotracker module (with the Frame rate 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.
****** – The results are given for a standard neural network capable of detecting an object sized at least 5% of the frame width/height. The results may differ for a neural network capable of detecting smaller objects (since more resources are required).