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To configure the Object tracker detection tooldetector, do the following:
- Go to the
Detection Tools- Detectors tab.
- Below the required camera, click Create… → Category: Trackers → Object tracker.
By default, the
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detector is enabled and set to detect moving objects in the frame, on the basis of which their tracks are created.
Some parameters are set for all sub-detectors of the the Object tracker simultaneously (see Recommendations for configuring the Object tracker and its sub-detectors).
If necessary, you can change the
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detector parameters. The list of parameters is given in the table:
| Parameter | Value | Description |
|---|
| Object features |
| Record objects tracking | Yes | By default, metadata is recorded into the database. To disable metadata recording, select the No value. | Note |
|---|
| To obtain metadata, the video is decompressed and analyzed, which results in a heavy load on the server and limits the number of video cameras that can be used on it. |
|
| No |
| Video stream | Main stream | If the camera supports multistreaming, select the stream for which detection is needed. Selecting a low-quality video stream allows you to reduce the server load.
| Note |
|---|
| To ensure the correct display of streams on a multi-stream camera, all video streams must have the same frame aspect ratio. |
|
| Other |
| Enable | Yes | By default, the parameter is enabled. To disable, select the No value |
| No |
| Name | Object tracker | Enter the |
detection tool | detector name or leave the default name |
| Decoder mode | Auto | Select a processing resource for decoding video streams. When you select a GPU, a stand-alone graphics card takes priority (when decoding with Nvidia NVDEC chips). If there is no appropriate GPU, the decoding |
will use uses the Intel Quick Sync Video technology. Otherwise, CPU resources |
will be are used for decoding |
| CPU |
| GPU |
| HuaweiNPU |
| Type | Object tracker | Name of the |
detection tool | detector type (non-editable field) |
Neural network filter
|
Enable filter
| Yes
| By default, the neural network filter is disabled. To enable a neural network filter to filter out parts of tracks, set the value to Yes (see Hardware requirements for neural analytics operation). For example, a neural network filter can process the results of the tracker and filter out false positives on a complex video image (foliage, glare, |
etc.A You can use a neural network filter |
|
can be used either only for the analysis of moving objects or only for the analysis of abandoned objects. You cannot use two neural network filters simultaneously. |
|
No
|
Moving object filter mode
| CPU | |
other - another processing resource than the CPU, this device
|
|
will carry the - carries most of the computing load. However, the CPU
|
|
will be the detection tool- the detector.
- It can take several minutes to launch the algorithm on NVIDIA GPU after you apply the settings. You can use caching to speed up future launches (see Optimizing the operation of neural analytics on GPU in Windows OS).
- Starting with Detector Pack 3.11, Intel HDDL and Intel NCS aren’t supported.
- Starting with Detector Pack 3.14, Intel Multi-GPU and Intel GPU 0-3 are supported.
|
|
| Nvidia GPU 0 |
| Nvidia GPU 1 |
| Nvidia GPU 2 |
| Nvidia GPU 3 |
| Intel NCS (not supported) |
| Intel HDDL (not supported) |
| Intel Multi-GPU |
| Intel GPU 0 |
| Intel GPU 1 |
| Intel GPU 2 |
| Intel GPU 3 |
| Huawei NPU |
Abandoned object filter mode
| CPU |
| Nvidia GPU 0 |
| Nvidia GPU 1 |
| Nvidia GPU 2 |
| Nvidia GPU 3 |
| Intel NCS (not supported) |
| Intel HDDL (not supported) |
| Intel Multi-GPU |
| Intel GPU 0 |
| Intel GPU 1 |
| Intel GPU 2 |
| Intel GPU 3 |
| Huawei NPU |
Moving object filter file
| | Select the required neural network. To obtain a neural network, contact AxxonSoft technical support. If the neural network file |
is not isn't selected or selected incorrectly, the filter |
will not workdoesn't work | Note |
|---|
| - You cannot specify the network file in Windows OS. You must place the neural network file locally, that is, on the same server where you install Axxon One.
- For correct neural network operation on Linux OS, place the corresponding file locally in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory or in the network folder with the corresponding access rights.
|
|
| Abandoned object filter file | |
Basic settings
|
Long-time abandoned object detection
| Yes
| By default, the parameter is disabled. To enable, select the Yes value. | Info |
|---|
| If you enable this and the Enable filter parameter, it can reduce the number of false positives during detection. |
|
No
|
Abandoned object detection
| Yes
| By default, the parameter is disabled. To enable, select the Yes value.
| Info |
|---|
| Objects abandoned for 10 seconds or longer |
|
will be |
No
|
Max. object height
| 100
| Set the maximum height and width of the detected object as a percentage of the frame size. The value must be in the range [0.05, 100].
| Note |
|---|
| If the Object calibration parameter is enabled in the tracker settings, then the maximum height and width of objects is set in decimeters and not as a percentage of the frame size. |
|
| Max. object width | 100
|
| Alarm on object's max. idle time in area | 60
| |
seconds—if seconds exceeding which the object |
remains idle for the time longer than the specified, it will be is detected. This value must be in the range [15, 1800]. | Info |
|---|
| This parameter is used only for the Long-time abandoned object detection. |
|
It is recommended to select We recommend selecting the parameter value starting from 15. |
|
| Min. object height | 2
| Set the minimum height and width of the detected object as a percentage of the height/width of the frame |
size. The value must be in the range [0.05, 100]. | Note |
|---|
| If the Object calibration parameter is enabled in the tracker settings, then the minimum height and width of objects is set in decimeters and not as a percentage of the frame size. |
|
| Min. object width | 2
|
Motion detection sensitivity
| 25
| Set the sensitivity of the motion sub-detectors in percentage. The higher the sensitivity, the |
more subtle change fewer changes in the frame |
will be are detected. The value must be in the range [0, 100] |
| Abandoned object detection sensitivity | 9
| Set the sensitivity for abandoned object detection and long-time abandoned object detection as a percentage.
The value must be in the range [ |
1This parameter The Abandoned object detection sensitivity parameter depends on the lighting conditions and |
|
must be chosen It is recommended to select We recommend selecting the parameter value starting from 20. |
|
Advanced settings
|
Auto sensitivity
| Yes
| |
the parameter the Auto sensitivity is enabled. To disable automatic adjustment of the sensitivity of |
the the Object tracker sub-detectors, select the No value.
|
It is recommended to enable We recommend enabling this parameter if the lighting changes significantly |
|
in FOV operation (for example, if the camera operates outdoors). |
|
No
|
Track lifespan (starting with Detector Pack 3.14)
| Yes | By default, the parameter is disabled. If you want to display the track lifespan for an object in seconds, select the Yes value |
| No |
Leveling rod height
| 20
| Set the height of the calibration object in decimeters. The value must be in the range [1, 100] |
Frame size change
| 1280
| By default, during the analysis, the frame is compressed to the specified size (by default, 1280 pixels on the larger side). The following algorithm is used: - If the original resolution on the larger side of the frame is greater than the resolution specified in the Frame size change parameter, then it is divided in half.
- If the resulting resolution becomes less than the specified one, then the algorithm stops and the resulting resolution
|
will be - is used.
- If the resulting resolution is still greater than the specified one, then it is divided in half again until it becomes
|
less than the resolution specified in the Frame size change parameter| Info |
|---|
| For example, the original video resolution is 2048x1536, the specified value is 1000. In this case, the original resolution |
|
will be is divided in half (512x384) twice |
|
, because after the first division, the value on the larger side of the frame |
|
will be is greater than the specified value (1024 > 1000).
If detection errors occur when using a higher resolution stream |
|
is used for detection and there are detection errors, it is recommended to reduce , we recommend reducing compression. |
|
Object calibration
| Yes
| By default, the parameter is disabled ( |
see see Configuring perspective). To estimate the real size of an object based on a simplified calibration system, select the Yes value
|
No
|
Camera position
| Wall
|
If you use a fish-eye camera, choose | To filter out false events when using a fisheye camera, select the correct location of the device |
to filter out false events is is not | isn't relevant for all other devices |
Ceiling
|
Antishaker
| Yes
| By default, the parameter is disabled. To reduce camera shake, select the Yes value. |
It is recommended to use We recommend using this parameter only when there is significant camera shake
|
| No |
By default, the entire frame is a detection area.If necessary, in the preview window, set:
| Info |
|---|
|
- For convenience of configuration, you can "freeze" the frame. Click the
 button. To cancel the action, click this button again. - The detection area is displayed by default. To hide it, click the
 button. To cancel the action, click this button again.
|
To save the parameters of the detection tooldetector, click the the Apply 
button. To cancel the changes, click the Cancel 
button.
The Object tracker detection tool is configuredConfiguring the Object tracker detector is complete. General parameters will be set for all its sub-detectors. If necessary, you can create and configure the necessary sub-detectors on the basis of the the Object tracker (see Abandoned object, Standard sub-detectors).
