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| - | ====== Pattern recognition ====== | ||
| - | ===== Classical ===== | ||
| - | |||
| - | ===Mean-Square Regression=== | ||
| - | =Objective= | ||
| - | Very fast if you already have a list of pixels you know belong to one contour, and you want to check if it fits to a parametric shape. | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ===Hough Transforms=== | ||
| - | |||
| - | ==Standard Hough Transform== | ||
| - | ==Randomized Hough Transform== | ||
| - | [Xu, | ||
| - | =Objective= | ||
| - | Improve speed, resolution, low memory needs, infinite scale. | ||
| - | =Quick Def= | ||
| - | If n parameters, take n points and only accumulate one point. | ||
| - | =References= | ||
| - | - [[http:// | ||
| - | - [[http:// | ||
| - | Vision_1998/ | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Connective Randomized Hough Transform== | ||
| - | [Kalvianen, | ||
| - | =Objective= | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | - [[http:// | ||
| - | fizSzdokumentitzSzjulkaisutzSztiedostotzSz1995zSzKalviainen_SCIA95_crht.pdf/ | ||
| - | connective-randomized-hough-transform.pdf| Main Article [EN] ]] | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Combinatorial Hough Transform== | ||
| - | =Objective= | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Adaptive Hough Transform== | ||
| - | [Ilingworth, | ||
| - | =Objective= | ||
| - | Improve speed and resolution. | ||
| - | =Quick Def= | ||
| - | First time at low resolution, then second time at higher resolution where there are peaks. | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Probabilistic Hough Transform== | ||
| - | [Kiryati, | ||
| - | =Objective= | ||
| - | Improve speed. | ||
| - | =Quick Def= | ||
| - | Only process n% of the pixels. | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Adaptive Probabilistic Hough Transform== | ||
| - | =Objective= | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Progressive Probabilistic Hough Transform== | ||
| - | =Objective= | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Hierarchical Hough Transform== | ||
| - | [Princen, | ||
| - | =Objective= | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Sampling Hough Transform== | ||
| - | =Objective= | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | - http:// | ||
| - | =Full Definition= | ||
| - | |||
| - | ==Generalized Hough Transform== | ||
| - | =Objective= | ||
| - | =Quick Def= | ||
| - | =References= | ||
| - | =Full Definition= | ||
| - | |||
| - | ===UpWrite method=== | ||
| - | =References= | ||
| - | - http:// | ||
| - | | ||
| - | ===Curvogram=== | ||
| - | |||
| - | |||
| - | ===== Learning ===== | ||
| - | |||
| - | ===Viola-Jones Detector=== | ||
| - | * with extended set of haar features | ||
| - | * Rotation Invariant | ||
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