How to use Autotag in PIX4Dcatch app - PIX4Dcatch

What are Autotags?

Autotags are targets that PIX4Dcatch can automatically detect and mark. They can be used as Ground Control Points (GCPs) or Manual Tie Points (MTPs), helping improve project accuracy while reducing the need for manual point marking. 

 Autotags can be combined with a set of known coordinates to function as Ground Control Points (GCPs). When a Point Collection containing surveyed coordinates is linked to the Autotags, PIX4Dcatch automatically associates each tag with its corresponding coordinate, marks them, and treats them as a GCP. If no known coordinates are linked to the Autotags, PIX4Dcatch considers them as Manual Tie Points (MTPs) and uses them to improve image alignment and reconstruction.

                               

Autotags cannot be purchased; they can be downloaded from the links below:

• A4 size PDF
  
  
• US Letter size PDF

Best Practices for Using Autotags in PIX4Dcatch

Placement Guidelines

Proper Autotag placement is critical for accurate detection and reliable results:

• Distribute Autotags evenly across the project area.
  
  
• Ensure Autotags are clean, flat, and not obstructed by shadows or objects.
  
  
• Avoid blurry images. Ensure each tag is clearly visible and sharp.
  
  
• Make sure tags are large enough to appear clearly in the captured images.
  
  
• Maintain a good image overlap so each tag appears in multiple images.
  
  
• Avoid placing unused Autotags within view, as they may interfere with detection.
  
  
• Do not place Autotags at the very edges of the project area. They may not appear in a sufficient number of images.

Tag Distribution Example

Think of your project area as a table, with Autotags as its legs. Clustered legs make it unstable, while evenly spaced ones keep it balanced. For best results, distribute Autotags evenly across the area and, if possible, place one near the center to enhance model stability.

Recommended setup:

• Minimum: 3 Autotags (required for processing).
  
  
• Recommended: 5–10 Autotags for improved accuracy.
  
  

Corridors: Offset the tags along the length and place a pair at each end.

How to enable the Tag Detection feature

PIX4Dcatch can automatically detect Autotags during image capture if the Tag Detection feature is enabled. Enabling this feature without importing a Point Collection for GCPs will create MTPs.

1. Go to Capture Mode.
2. Tap the Tools menu.
3. Select Tag Detection.
   
   
4. Enable Detect Autotags.
   
   
   

A confirmation will appear showing that Autotag detection is active.

   

How to enable GCPs with the Tag Detection feature

In PIX4Dcatch, a set of Ground Control Points (GCPs) is managed through a Point Collection. For Autotags to be used as GCPs, a Point Collection containing known surveyed coordinates must be imported and linked to the Autotags. 

PIX4Dcatch RTK can be used to capture GCPs directly in the field, or known coordinates can be imported into the PIX4Dcatch app via a Point Collection. For more information, visit How to import and mark Ground Control Points (GCPs) in PIX4Dcatch.

To enable the tag detection feature with GCPs, follow the steps below.

1.  After the Tag Detection feature is enabled, tap Import Point Collection.
   
2. Select Point Collection from the list.
   
   
3. Once imported, tap Done.
   

Example:

• PointName_1 corresponds to Autotag 01
• PointName_2 corresponds to Autotag 02
• PointName_3 corresponds to Autotag 03

During Capture

While moving around the site:

• PIX4Dcatch will mark detected Autotags in real-time.
  
  
• Tags with green labels indicate valid detections.
  
  
• Below the Signal Indicator dialog, the total number of successfully marked Autotags and the number of point entries in the Point Collection are displayed.
  
  

Optimizing Autotag Detection

After capture, PIX4Dcatch gives the option to optimize Autotag detection. This step improves marker precision and strengthens the 3D model reconstruction. Autotag Detection can be optimized in two ways: either manually through the Optimize menu available in the project, or automatically during processing when PIX4Dcatch applies optimization based on the project settings and dataset size. 

How to Optimize Autotag Detection

1. Tap the more options icon in the upper-right corner of the project. 
2. Select Optimize.
   
   
3. A list of optimization options will appear. Select one or more options; multiple optimization tasks can be processed concurrently in a single optimization run: 
   1. Autotag Detection:  Improves the accuracy of 3D model reconstruction.
   2. Depth Alignment:  Helps remove or reduce double surfaces in the model. 
   3. Point Cloud (iOS with LiDAR only): Generates a point cloud from the captured data. If Point Cloud is selected, the two processing options will be available.
      
      Dense Point Cloud: Generates a highly detailed point cloud with a large number of points. It delivers greater detail but requires longer processing time. 
      
      Sparse Point Cloud: Generates a lighter point cloud with fewer points. It processes faster but contains less detail. 

       4. Tap the Optimize icon  . The optimization process can be canceled;                      however, doing so may risk corrupting the project.

 Optimize Autotags During Processing

PIX4Dcatch allows automatic optimization of Autotag detection when processing a project. Enabling this option ensures improved accuracy without requiring manual intervention. 

To configure automatic optimization when processing:

1. Go to Main Menu > Project Settings.
   
   
2. Tap Optimize Autotags When Processing.
   
   
3. Choose one of the following:
   
   
         

Ask each time – Display a prompt before optimizing.
Skip – Do not optimize when processing.

Always – Automatically optimize upon processing.