For further context, one common scenario where Visual Object Detection can make a major impact is testing an interactive X-Y canvas, such as:
- A drawing or sketch pad
- A chart where users drag points to new positions
- A design surface where objects can be moved or resized
- Any UI where elements are placed dynamically on a grid
In these situations, traditional object recognition often struggles because:
- The elements are rendered visually on a canvas, not as standard UI components
- Their positions change constantly
- Objects may overlap, look similar, or appear only temporarily
- There are no stable identifiers or accessible properties
This can lead to test instability, false positives, or situations where the object can’t be identified at all.
With AI based VOD, our goal is to reliably recognize these visual elements even when they move, change appearance, or exist only as pixels on the screen.
Staff