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Accurate and low complex cell histogram generation by bypass the gradient of pixel computation

机译:通过绕过像素计算的梯度来准确且低复杂度地生成直方图

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Histogram of Oriented Gradient (HOG) is a popular feature description for the purpose of object detection. However, HOG algorithm requires a high performance system because of its complex operation set. In HOG algorithm, the cell histogram generation is one of the most complex part, it uses inverse tangent, square, square root, floating point multiplication. In this paper, we propose an accurate and low complex cell histogram generation by bypass the gradient of pixel computation. It employs the bin's boundary angle method to determine the two quantized angles. However, instead of choosing an approximate value of tan, the nearest greater and the nearest smaller of each tan value from the ratios between pixel's derivative in y and x direction are used. The magnitudes of two bins are the solutions of a system of two equations, which represents the equality of the gradient of a pixel and its two bins in both vertical and horizontal direction. The proposed method spends only 30 addition and 40 shift operations to caculate two bins of a pixel. Simulation results show that the percentage of error when reconstructing the differences in x and y direction are always less than 2% with 8-bit length of the fractional part. Additionally, manipulating the precision of gradient magnitude is very simple by pre-defined sine and cosine values of quantized angles. The synthesis results of a hardware implementation of the proposed method occupy 3.57 KGEs in 45nm NanGate standard cell library. The hardware module runs at the maximum frequency of 400 MHz, and the throughput is 0.4 pixels for a single module. It is able to support 48 fps with 4K UHD resolution.
机译:定向梯度直方图(HOG)是用于物体检测的流行特征描述。然而,HOG算法由于其复杂的操作集而需要高性能的系统。在HOG算法中,单元格直方图生成是最复杂的部分之一,它使用反正切,平方,平方根,浮点乘法。在本文中,我们通过绕过像素计算的梯度,提出了一种精确且低复杂度的细胞直方图生成方法。它采用bin的边界角方法确定两个量化角。但是,不是选择tan的近似值,而是使用从y和x方向上的像素导数之间的比率得出的每个tan值的最近的较大值和最近的较小值。两个面元的大小是两个方程式系统的解,表示一个像素及其两个面元在垂直和水平方向上的梯度相等。所提出的方法仅花费30个加法和40个移位操作即可计算一个像素的两个bin。仿真结果表明,在小数部分为8位的情况下,重建x和y方向差异时的错误百分比始终小于2%。另外,通过预定义的量化角度的正弦和余弦值,操纵梯度幅度的精度非常简单。该方法的硬件实现的综合结果在45nm NanGate标准单元库中占据3.57 KGE。硬件模块的最大频率为400 MHz,单个模块的吞吐量为0.4像素/ ns。它能够以4K UHD分辨率支持48 fps。

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