Optimizing Image Target Tracking

To ensure the highest quality image target tracking experience, be sure to follow these guidelines when selecting an image target.

Preparation

Before training the Image Targets, you must prepare the images in digital format. The available formats are

• .jpg/jpeg

• .png

• .bmp

A good Image Target will have certain visual features that enables accurate pose estimation and stable tracking :

Properties	Explanation
Distinctive pattern	A texture with evenly distributed and distinctive visual features (e.g. corners, blobs)
No repetitive pattern	Textures with no similar patterns repeating in space
High contrast	Image with high contrast
Non-reflective	Print on a matte surface that will not reflect light when printed

Target Image Best Practices:

Image Targets that possess the following attributes will enable the best detection and tracking performance from the the SQUARS viewer. A basic rule is that complex and detailed images on well lit flat surfaces work best.

Examples of good target images:

Examples of bad target images:

Target Rating

Image Targets are detected by analyzing the inherent features extracted from the target image and comparing them in real-time with the features in the live camera image. Targets are given a rating of either 'good', 'normal', or 'bad'. Although targets with lower ratings ('bad' or 'normal') can still be detected and tracked, it is advisable to use a 'good' rating target.

To create a target that is accurately detected, you should use images according to the above attributes for an ideal Image Target.