Parameters and Presets
Parameters
Recipe parameters for 3D Object Tracking and their descriptions are summarized in the table below.
| Preset Group | Parameter Name | Min Value | Max Value | Description |
|---|---|---|---|---|
| Detection | Average Object Radius (Remove Background only) | 0 | 1,000 | Specifies the radius of a typical object in the image for object enhancement and background removal; a lower value will preserve smaller objects |
| Min Edge Intensity | 0 | 255 (8-bit) 65,535 (16-bit) | Specifies the minimum object intensity that is typically found at the edge of the object for detection; when Remove Background is enabled, this parameter value is used to specify the minimum object intensity on the enhanced image; a lower value will detect bigger and more objects | |
| Partition | Object Radius | 0 | 1,000 | Specifies the range of objects to be included in the analysis results based on the radius of the detected objects |
| Smoothing Factor | 0 | 10 | Adjusts the amount of smoothing applied to the surface reconstructions of the detected objects; a lower value will generate surfaces with greater similarity to the input image | |
Min Edge-to-Center Distance (Apply Partition only) | 0 | 1,000 | Specifies the minimum distance from the center of an object to the edge that is touching its closest neighboring object; this parameter is enabled only when Apply Partition is enabled; a lower value will apply object partitioning more aggressively, resulting in smaller, more uniform objects | |
| Tracking | Minimum Track Length | 1 | 100 | Specifies the minimum number of time frames before a detected object is considered a valid track; a lower value will generate more, and often shorter, tracks |
| Maximum Search Range | 0 | 1,000 | Specifies the maximum distance for track-point matchmaking between successive time frames; a higher value will expand the search distance for fast-moving cells | |
| Motion vs Intensity | 0 | 10 | Adjusts the relative weighting between motion and object intensity for track-point matchmaking between successive frames; a value of 5 will apply equal weights to motion and intensity for matchmaking | |
| Track Lineage Option | Not applicable | Toggles tracking of object division and lineages | ||
| Matchmaking Option | Not applicable | Toggles the tracking algorithm used for track-point matchmaking between time points; the available options are Greedy Matching and Hungarian Matching | ||
Tutorial
Before beginning the tutorial, please download the 3D Object Tracking Demo image. For information on how to select presets or modify parameter values, please refer to the tutorial on how to use the Recipe Console.
- Unzip the demo file and load the demo image, 3DObjTrackDemo.aivia.tif, into Aivia
- In the Recipe Console, click on the Recipe selection dropdown menu and select the 3D Object Tracking recipe
- Click on the Small button for the Partition preset and the Intensity button for the Tracking preset, leave the Detection preset as is for now
- Click on the Show Advanced Interface icon
to expand the Recipe Console - Under the Detection preset, click on the Switch Recipe Operations icon
next to the Min Edge Intensity parameter to show the list of available recipe operations; select the Remove Background option from the dropdown menu - Change the parameters listed below to the specified values, leaving the others intact:
- Detection
- Average Object Radius: 4
- Min Edge Intensity: 3
- Partition
- Min Edge-to-Center Distance: 4
- Detection
- Click the Start button or press the F4 key on your keyboard to begin applying the recipe to the image
The surface reconstructions can be viewed in 3D View, while all tracks can be viewed in both 2D and 3D Views. Please note that in 2D View, tracks that are out of the current plane are also overlaid on the image.
Results
| 3D Object Tracking results |
Image credits
Stegmaier J, Mikut R. (2017) Fuzzy-based propagation of prior knowledge to improve large-scale image analysis pipelines. PLoS One. 12(11):e0187535. doi:10.1371/journal.pone.0187535