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@ -43,11 +43,19 @@ points than for SURF points. |
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In short, BRIEF is a faster method feature descriptor calculation and matching. It also provides |
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high recognition rate unless there is large in-plane rotation. |
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STAR(CenSurE) in OpenCV |
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------ |
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STAR is a feature detector derived from CenSurE. |
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Unlike CenSurE however, which uses polygons like squares, hexagons and octagons to approach a circle, |
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Star emulates a circle with 2 overlapping squares: 1 upright and 1 45-degree rotated. These polygons are bi-level. |
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They can be seen as polygons with thick borders. The borders and the enclosed area have weights of opposing signs. |
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This has better computational characteristics than other scale-space detectors and it is capable of real-time implementation. |
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In contrast to SIFT and SURF, which find extrema at sub-sampled pixels that compromises accuracy at larger scales, |
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CenSurE creates a feature vector using full spatial resolution at all scales in the pyramid. |
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BRIEF in OpenCV |
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--------------- |
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Below code shows the computation of BRIEF descriptors with the help of CenSurE detector. (CenSurE |
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detector is called STAR detector in OpenCV) |
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Below code shows the computation of BRIEF descriptors with the help of CenSurE detector. |
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note, that you need [opencv contrib](https://github.com/opencv/opencv_contrib)) to use this. |
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@code{.py} |
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