Parametric Feature Detection
Most visual features are parametric in nature, including edges, lines, corners and junctions. We have developed an algorithm to automatically construct detectors for arbitrary parametric features. To maximize robustness we use realistic multi-parameter feature models and incorporate optical and sensing effects. Each feature is represented as a densely sampled parametric manifold in a low-dimensional subspace of a Hilbert space. During detection, the vector of intensity values in a window about each pixel in the image is projected into the subspace. If the projection lies sufficiently close to the feature manifold, the feature is detected and the location of the closest manifold point yields the feature parameters. The concepts of parameter reduction by normalization, dimension reduction, pattern rejection and heuristic search are all employed to achieve the required efficiency. Detectors have been constructed for five features, namely, step edge (five parameters), roof edge (five parameters), line (six parameters), corner (five parameters) and circular disc (six parameters).


"Global Measures of Coherence for Edge Detector Evaluation,"
S. Baker and S.K. Nayar,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
Vol. 2, pp. 373-379, Jun. 1999.
[PDF] [bib] [©]

"Parametric Feature Detection,"
S. Baker, S.K. Nayar and H. Murase,
International Journal on Computer Vision,
Vol. 27, No. 1, pp. 27-50, Mar. 1998.
[PDF] [bib] [©]

"Parametric Feature Detection,"
S.K. Nayar, S. Baker and H. Murase,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
pp. 471-477, Jun. 1996.
[PDF] [bib] [©]


  Detection of Edges and Corners:
In this example our edge and corner detectors are used to find edges (blue) and corners (red) in the image.
  Detection of Lines and Curves:
In this example our line and curve detectors are used to find lines (green) and curves (yellow) in the image.


EdgeVal: Edge Detector Evaluation Database and Evaluation Code
This database and software provide a means to evaluate the performance of any edge detector based on global measures of coherence.

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