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ai:methods:pattern-recognition [2013/09/19 16:40] 127.0.0.1 external edit |
ai:methods:pattern-recognition [2022/04/07 22:33] (current) cyril import private |
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| - | ====== Pattern recognition ====== | + | ====== Pattern recognition |
| - | ===== Classical | + | |
| - | ===Mean-Square Regression=== | + | ====Mean-Square Regression==== |
| - | =Objective= | + | ==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. | 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= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ===Hough Transforms=== | + | ====Hough Transforms==== |
| - | ==Standard Hough Transform== | + | ===Standard Hough Transform=== |
| - | ==Randomized Hough Transform== | + | ===Randomized Hough Transform=== |
| [Xu, | [Xu, | ||
| - | =Objective= | + | ==Objective== |
| Improve speed, resolution, low memory needs, infinite scale. | Improve speed, resolution, low memory needs, infinite scale. | ||
| - | =Quick Def= | + | ==Quick Def== |
| If n parameters, take n points and only accumulate one point. | If n parameters, take n points and only accumulate one point. | ||
| - | =References= | + | ==References== |
| - [[http:// | - [[http:// | ||
| - [[http:// | - [[http:// | ||
| Vision_1998/ | Vision_1998/ | ||
| - | =Full Definition= | + | ==Full Definition== |
| - | ==Connective Randomized Hough Transform== | + | ===Connective Randomized Hough Transform=== |
| [Kalvianen, | [Kalvianen, | ||
| - | =Objective= | + | ==Objective== |
| - | =Quick Def= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - [[http:// | - [[http:// | ||
| fizSzdokumentitzSzjulkaisutzSztiedostotzSz1995zSzKalviainen_SCIA95_crht.pdf/ | fizSzdokumentitzSzjulkaisutzSztiedostotzSz1995zSzKalviainen_SCIA95_crht.pdf/ | ||
| Line 34: | Line 33: | ||
| =Full Definition= | =Full Definition= | ||
| - | ==Combinatorial Hough Transform== | + | ===Combinatorial Hough Transform=== |
| - | =Objective= | + | ==Objective== |
| - | =Quick Def= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ==Adaptive Hough Transform== | + | ===Adaptive Hough Transform=== |
| [Ilingworth, | [Ilingworth, | ||
| - | =Objective= | + | ==Objective== |
| Improve speed and resolution. | Improve speed and resolution. | ||
| - | =Quick Def= | + | ==Quick Def== |
| First time at low resolution, then second time at higher resolution where there are peaks. | First time at low resolution, then second time at higher resolution where there are peaks. | ||
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ==Probabilistic Hough Transform== | + | ===Probabilistic Hough Transform=== |
| [Kiryati, | [Kiryati, | ||
| - | =Objective= | + | ==Objective== |
| Improve speed. | Improve speed. | ||
| - | =Quick Def= | + | ==Quick Def== |
| Only process n% of the pixels. | Only process n% of the pixels. | ||
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ==Adaptive Probabilistic Hough Transform== | + | ===Adaptive Probabilistic Hough Transform=== |
| - | =Objective= | + | ==Objective== |
| - | =Quick Def= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ==Progressive Probabilistic Hough Transform== | + | ===Progressive Probabilistic Hough Transform=== |
| - | =Objective= | + | ==Objective== |
| - | =Quick Def= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ==Hierarchical Hough Transform== | + | ===Hierarchical Hough Transform=== |
| [Princen, | [Princen, | ||
| - | =Objective= | + | ==Objective== |
| - | =Quick Def= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ==Sampling Hough Transform== | + | ===Sampling Hough Transform=== |
| - | =Objective= | + | ==Objective== |
| - | =Quick Def= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - http:// | - http:// | ||
| =Full Definition= | =Full Definition= | ||
| - | ==Generalized Hough Transform== | + | ===Generalized Hough Transform=== |
| - | =Objective= | + | ==Objective== |
| - | =Quick Def= | + | ==Quick Def== |
| - | =References= | + | ==References== |
| - | =Full Definition= | + | ==Full Definition== |
| - | ===UpWrite method=== | + | ====UpWrite method==== |
| - | =References= | + | ==References== |
| - http:// | - http:// | ||
| + | | ||
| + | ====Curvogram==== | ||
| + | |||
| + | |||
| + | ====== Pattern recognition - Learning ====== | ||
| + | |||
| + | =====Viola-Jones Detector===== | ||
| + | [Viola, | ||
| + | ==Quick Def== | ||
| + | Cascade of boosted classifiers based on Haar-like features. | ||
| + | ==References== | ||
| + | - {{|2001, | ||
| + | |||
| + | ====with Extended Set of Haar features==== | ||
| + | [Lienhart, | ||
| + | ==Quick Def== | ||
| + | Basic features are line features, edge features, and center surrounded features, all of them horizontal or vertical. The extended set also includes 45° rotated features, and an optional diagonal feature. | ||
| + | ==References== | ||
| + | - {{|2002, | ||
| + | |||
| + | ====Stumps or CART trees==== | ||
| + | ==Quick Def== | ||
| + | Stumps are single node trees, and CART (Classification And Regression Trees) more complex trees with a few nodes (4 or 5). | ||
| + | |||
| + | ====Rotation Invariant==== | ||
| + | ==References== | ||
| + | - | ||
| + | |||
| + | ====Multiview==== | ||
| + | ===Parallel Cascades=== | ||
| + | ==Objective== | ||
| + | Obvious way to deal with multiview. | ||
| + | ==Quick Def== | ||
| + | {{ parallel-cascades.png | ||
| + | ===Pyramid Cascades=== | ||
| + | ==Objective== | ||
| + | ==Quick Def== | ||
| + | {{ pyramid-cascades.png | ||
| + | ==References== | ||
| + | - {{|2002, | ||
| - | ===== Learning | + | ===Tree Cascades=== |
| + | ==Objective== | ||
| + | ==Quick Def== | ||
| + | {{ tree-cascades.png | ||
| + | ==References== | ||
| + | - {{|2003, | ||
| + | ===Vector Boosting=== | ||
| + | ==Objective== | ||
| + | ==Quick Def== | ||
| + | ==References== | ||
| + | - {{|2005, | ||
