Accurate Junction Detection and Characterization in Natural Images
Accurate junction detection and characterization are of primary importance for several aspects of scene analysis, including depth recovery and motion analysis. In this work, we introduce a generic junction analysis scheme. The first asset of the proposed procedure is an automatic criterion for the d...
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| Veröffentlicht in: | International journal of computer vision 2014, Vol.106 (1), p.31-56 |
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| creator | Xia, Gui-Song Delon, Julie Gousseau, Yann |
| description | Accurate junction detection and characterization are of primary importance for several aspects of scene analysis, including depth recovery and motion analysis. In this work, we introduce a generic junction analysis scheme. The first asset of the proposed procedure is an automatic criterion for the detection of junctions, permitting to deal with textured parts in which no detection is expected. Second, the method yields a characterization of L-, Y- and X- junctions, including a precise computation of their type, localization and scale. Contrary to classical approaches, scale characterization does not rely on the linear scale-space. First, an
a contrario
approach is used to compute the meaningfulness of a junction. This approach relies on a statistical modeling of suitably normalized gray level gradients. Then, exclusion principles between junctions permit their precise characterization. We give implementation details for this procedure and evaluate its efficiency through various experiments. |
| doi_str_mv | 10.1007/s11263-013-0640-1 |
| format | Article |
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a contrario
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a contrario
approach is used to compute the meaningfulness of a junction. This approach relies on a statistical modeling of suitably normalized gray level gradients. Then, exclusion principles between junctions permit their precise characterization. We give implementation details for this procedure and evaluate its efficiency through various experiments.</description><subject>Analysis</subject><subject>Applied sciences</subject><subject>Artificial Intelligence</subject><subject>Computation</subject><subject>Computer Imaging</subject><subject>Computer Science</subject><subject>Computer science; control theory; systems</subject><subject>Computer Vision and Pattern Recognition</subject><subject>Exact sciences and technology</subject><subject>Image Processing and Computer Vision</subject><subject>Image processing systems</subject><subject>Localization</subject><subject>Pattern Recognition</subject><subject>Pattern Recognition and Graphics</subject><subject>Pattern recognition. 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| subjects | Analysis Applied sciences Artificial Intelligence Computation Computer Imaging Computer Science Computer science control theory systems Computer Vision and Pattern Recognition Exact sciences and technology Image Processing and Computer Vision Image processing systems Localization Pattern Recognition Pattern Recognition and Graphics Pattern recognition. Digital image processing. Computational geometry Sensors Studies Vision Vision systems |
| title | Accurate Junction Detection and Characterization in Natural Images |
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