计算机视觉:考虑颜色的 SURF(加速鲁棒功能)
是否有可能增强加速鲁棒特征(SURF)计算机视觉算法,使其能够区分均匀分布和形状不同的颜色物体?
我正在寻找研究论文或任何其他试图增强 SURF 的来源,以便它可以区分具有不同颜色的相同物体。
Is it possible to enhance the Speeded Up Robust Features (SURF) Computer Vision algorithm so that it can differentiate equally distributed and shaped objects with different colors?
I am looking for research papers or any other sources that try to enhance SURF so that it can differentiate the same objects with different colors.
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Color-SURF:具有本地内核颜色直方图的 surf 描述符
Color-SURF: A surf descriptor with local kernel color histograms
与向算法添加颜色相比,转换图像然后在每个单一颜色缩放器图像上运行算法通常更容易。
值得考虑的是在另一个颜色空间而不是 RGB 中执行此操作 - 取决于您要查找的内容,在 HSV 或 YUV(至少是 UV)部分中执行此操作可能有意义。
Rather than add color to the algorithm it's often easier to convert the image and then run the algorithm on each single color scaler image.
It's worth looking at doing this in another color space rather than RGB - depending on what you are trying to find, doing it in HSV or YUV (at least the UV) parts might make sense.
我认为向 SURF 添加颜色信息可能会稍微提高性能,但不会显着
I think the addition of color information to the SURF may enhance the performance a little, but not significantly