Quite surprised to see something of this genre discussed here without any mention of the obvious benefits in industrial process.
By normalizing the spatial representation of the captured image, it is possible to perform quantitative analysis without any additional processing overhead or associated temporal delay.
Presumably sharp focus and a lack of distortion would grant similar benefits when training machine learning for visual applications.
Source: Own multiple books on the early era of photography when tilt-shift was a normal feature ("view cameras") and have designed a fair number of autonomous optical systems. The best book I have, for the benefit of others, is View Camera Technique (7th Edition).
By normalizing the spatial representation of the captured image, it is possible to perform quantitative analysis without any additional processing overhead or associated temporal delay.
Presumably sharp focus and a lack of distortion would grant similar benefits when training machine learning for visual applications.
Source: Own multiple books on the early era of photography when tilt-shift was a normal feature ("view cameras") and have designed a fair number of autonomous optical systems. The best book I have, for the benefit of others, is View Camera Technique (7th Edition).