Knowledge Base

Calculation of the Center-Point

For New Experiments

In all new experiments, the subject's center-point is determined using the area of the blob that indicates the detected subject. The x, y coordinates of the center-point are the average of the x, y coordinates of each pixel in the blob. If the tail is detected, that contributes to the position of the center-point.

Experiments Created in EthoVision XT 14 and Earlier

If your experiment was created in a previous EthoVision XT version, and you use one of the For Occlusions methods, you can choose whether to use the detected area (as described above) or the shape model. Choose Use center of model (XT14 and earlier).

The x, y coordinates of the center-point are the average of the pixel coordinates of the model fit over the detected subject. In many situations the model has a more regular shape than the detected area.

Choose Use center of model (XT14 and earlier) to keep compatibility with older experiments. Note that if detection or the model parameters are not optimal, the model may differ greatly from the subject's image. In this case the center point may shift compared to the expected position, which may add up distance moved over time.

If that happens often, choose Use center of detected area. Or, for multi-subject tracking, adjust the modeled subject size. See Advanced Detection Settings: Subject Size (Multiple Animals per Arena).

See Also

• Adjust the Settings for Nose-Tail Base Detection (Contour-Based)
• Subject Contour for Nose-Tail Base Detection

Advanced Detection Settings: Smoothing

Aim

To make tracking less dependent on noise.

• Use Video pixel smoothing to remove fine-grained noise in the video image.
• Use Dropped frames correction to compensate for irregular frame rate in low-end cameras.
• Use Track noise reduction to reduce jitter of the body points and smooth out the track during acquisition.

How to Access These Options

In the Detection Settings window, under Advanced, click Smoothing.

Procedure

• Video Pixel Smoothing
• Dropped Frames Correction
• Track Noise Reduction

See Also

• Smooth the Tracks After Acquisition

Video Pixel Smoothing

Aim

The Video pixel smoothing option reduces the difference between adjacent pixels prior to detection, by smudging the image — that is, replacing the gray scale value of each pixel with the median of the surrounding pixels.

Background Information

In the following example, a bright pixel with gray value 240 is surrounded by darker pixels:

• If you select Video pixel smoothing = Low, that pixel gets the median value calculated among the 8 nearest pixels plus that pixel itself. In that case the median is 150, so that pixel will look darker.
• If you specify Video pixel smoothing = Medium, the median is calculated over the 24 nearest pixels plus the pixel itself.
• If you specify Video pixel smoothing = High, an even bigger group of surrounding pixels is considered.

Procedure

1. In the Detection Settings, under Advanced, open Smoothing.
2. Next to Video pixel smoothing, choose one of the values:
   • None (default): No pixel smoothing. The video image is analyzed for subject detection as it is.
   • Low: Each pixel is blended with the 8 nearest pixels (pixel distance = 1).
   • Medium: Each pixel is blended with the 24 nearest pixels (pixel distance 1 or 2).
   • High: Each pixel is blended with the 48 nearest pixels (pixel distance 1, 2 or 3).

Notes

• Select a moderate Video pixel smoothing value or leave None selected if adjacent pixels in the background are relatively constant. Using more surrounding pixels for the smoothing effect does not bring better results.
• Select a high Video pixel smoothing value if adjacent pixels in the background are on average very different — for example, when the cage's bedding material looks grainy. In such cases you need to smooth each pixel using more surrounding pixels to compensate for this variation.
• A high Video pixel smoothing level requires a significant amount of processor capacity.
• Using Video pixel smoothing may result in losing information in the video image that is important for detection, such as sharp borders of subjects.
• Pixel smoothing does not affect Color marker tracking. It does affect detecting the body contour in Marker assisted tracking.

See Also

• Advanced Detection Settings: Smoothing