Using Multiple Images
Identifieur interne : 000153 ( Main/Exploration ); précédent : 000152; suivant : 000154Using Multiple Images
Auteurs : Peter Corke [Australie]Source :
- Springer Tracts in Advanced Robotics [ 1610-7438 ]
Abstract
Abstract: In the previous chapter we learnt about corner detectors which find particularly distinctive points in a scene. These points can be reliably detected in different views of the same scene irrespective of viewpoint or lighting conditions. Such points are characterised by high image gradients in orthogonal directions and typically occur on the corners of objects. However the 3-dimensional coordinate of the corresponding world point was lost in the perspective projection process which we discussed in Chap. 11 - we mapped a 3-dimensional world point to a 2-dimensional image coordinate. All we know is that the world point lies along some ray in space corresponding to the pixel coordinate, as shown in Fig. 11.1. To recover the missing third dimension we need additional information. In Sect. 11.2.3 the additional information was camera calibration parameters plus a geometric object model, and this allowed us to estimate the object’s 3-dimensional pose from the 2-dimensional image data.
Url:
DOI: 10.1007/978-3-642-20144-8_14
Affiliations:
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<front><div type="abstract" xml:lang="en">Abstract: In the previous chapter we learnt about corner detectors which find particularly distinctive points in a scene. These points can be reliably detected in different views of the same scene irrespective of viewpoint or lighting conditions. Such points are characterised by high image gradients in orthogonal directions and typically occur on the corners of objects. However the 3-dimensional coordinate of the corresponding world point was lost in the perspective projection process which we discussed in Chap. 11 - we mapped a 3-dimensional world point to a 2-dimensional image coordinate. All we know is that the world point lies along some ray in space corresponding to the pixel coordinate, as shown in Fig. 11.1. To recover the missing third dimension we need additional information. In Sect. 11.2.3 the additional information was camera calibration parameters plus a geometric object model, and this allowed us to estimate the object’s 3-dimensional pose from the 2-dimensional image data.</div>
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