Abstract
Generally it is impossible to determine the size of an object from a single image due to the depth-scale ambiguity
problem. However, with knowledge of the geometry of the scene and the existence of known reference
dimensions in the image, it is possible to infer the real world dimensions of objects with only a single image.
In this paper, we investigate different methods of automatically determining the dimensions of cuboids
(rectangular boxes) from a single image, using a novel reference target. In particular, two approaches will be
considered: the first will use the cross-ratio projective invariant and the other will use the planar homography.
The accuracy of the measurements will be evaluated in the presence of noise in the feature points. The effects
of lens distortions on the accuracy of the measurements will be investigated. Automatic feature detection
techniques will also be considered.
problem. However, with knowledge of the geometry of the scene and the existence of known reference
dimensions in the image, it is possible to infer the real world dimensions of objects with only a single image.
In this paper, we investigate different methods of automatically determining the dimensions of cuboids
(rectangular boxes) from a single image, using a novel reference target. In particular, two approaches will be
considered: the first will use the cross-ratio projective invariant and the other will use the planar homography.
The accuracy of the measurements will be evaluated in the presence of noise in the feature points. The effects
of lens distortions on the accuracy of the measurements will be investigated. Automatic feature detection
techniques will also be considered.
| Original language | Undefined/Unknown |
|---|---|
| Pages | 85-90 |
| Publication status | Published - 2007 |