• [学习笔记] CS131 Computer Vision: Foundations and Applications:Lecture 2 颜色和数学基础


    大纲

    what is color?

    • The result of interaction between physical light in the environment and our visual system.
    • A psychological property of our visual experiences when we look at objects and lights, not a physical property of those objects or lights.

     Human encoding of color

    Color Spaces

    • linear space: RGB/CIE XYZ
    • nolinear space: HSV

    Use of color in computer vision:

    • color histogram for indexing and retrieval
    • skin detection
    • nude people detection
    • image segmentation and retrieval
    • build apperance models for tracking
    • ...

    Linear Algebra Primer: Vectors and Matrix

    1. 向量

    列向量:$v in R^{n*1} v = egin{bmatrix} v_1 \ v_2\ cdot \ cdot \ cdot \ v_n end{bmatrix}$

    行向量:$v^T in R^{1*n} v^T = [v_1 v_2 ... v_n]$  (T转置运算符)

    向量使用:点的空间表示;表示数据,没有空间意义,但是计算仍然有意义

    2. 矩阵

    矩阵运算:addition, scaling

    矩阵范数:

    one norm:$||x||_1 = sum_{i=1}^n |x_i| $

    two norm:$||x||_2 = sqrt{sum_{i=1}^n x_i^2}

    infinity norm: $||x||_inf = max |x_i|$

    general P norm:||x||_p = (sum_{i=1}^n x_i^p)^1/p$

    matrix norm:||A||_F = sqrt{sum_{i=1}^m sum_{j = 1}^n A_ij^2 = sqrt{tr(A^TA)}$

    矩阵的秩:

    • $det(AB) = det(BA)$
    • $det(A^-1) = frac{1}{det(A)}$
    • $det(A^T) = det(A)$
    • $det(A) = 0$ 当且仅当$A$是奇异的

    矩阵的迹:对角元素的和

    特殊矩阵: 

    • 单位矩阵(Identity Matrix):对角元素为0,其他元素为1
    • 对角矩阵(diagonal matrix):非对角元素为0
    • 对称矩阵(Symmetric Matrix):$A^T = A$
    • 反对称矩阵(Skew-symmetric Matrix) $A^T = -A$
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  • 原文地址:https://www.cnblogs.com/vincentcheng/p/7930389.html
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