Hardware implementation of aggregated channel features for ADAS
Hardware implementation of aggregated channel features for ADAS
复制标题
ADAS 聚合通道功能的硬件实现
DOI：
10.1109/isocc.2016.7799844
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Hweihn Chung
中科院分区：
文献类型：
--
作者：
Hohyon Song;Bosun Jeong;Hyunkyu Choi;Taeho Cho;Hweihn Chung
在本文中，我们提出了在半导体级实现的硬件检测器架构，以实现更高的速度和性能，有效地作为ADAS视觉系统的预处理器相比，现有的解决方案，这是由ECU侧只或S/W实施的目的。在这里，该架构代表了更高的速度作为真实的时间，我们实现了一个硬件多尺度行人检测器操作在真实的时间（30 fps的640×480图像，全搜索）和性能作为ACF为基础的检测算法在一个高度集成的方式。其先进的ADAS算法最终可大幅提高检测率。为了有效的方法，我们直接构建图像金字塔，而不是使用附近尺度的近似特征，以提供更高的精度。为了有效地实现这一点，我们将探测器分为硬件和软件两部分。换句话说，H/W部分生成金字塔图像并提取特征，然后进行分类。S/W部分使用NMS对H/W分类结果进行聚类。作为仿真结果，在INRIA DB中，性能为18%@10-1FPPI。根据定义良好的系统划分，它提供了更快的计算和确保更高的检测率。
In this paper, we propose the hardware detector architecture implemented in the semiconductor level to achieve the higher speed and performance efficiently as pre-processor for ADAS vision system compared to the existing solution which is done by ECU side only or S/W implemented intently. Herein the architecture represents the higher speed as real time that we implement a hardware multi-scale pedestrian detector operating in real time (30fps on 640×480 images, full-search) and performance as ACF based for detection algorithm in a highly integrated manner. Its advanced ADAS algorithms deliver highly improved detection rate eventually. For the efficient method, we construct the image pyramid directly rather than using the approximate features at nearby scale for providing greater accuracy. To actualize it in an effective way, we design the detector separately as two parts - H/W part and S/W part. In other words, H/W part generates pyramid images and extracts features then does classification. S/W part does clustering from the H/W classification result using NMS. As a simulation result, the performance is 18%@10-1FPPI in the INRIA DB. According to well-defined system partitioning, it offers faster calculation and securing higher detection rate.
DOI：
10.1109/tpami.2011.155
发表时间：
2012-04-01
影响因子：
23.6
作者：
Dollar, Piotr;Wojek, Christian;Perona, Pietro
通讯作者：
Perona, Pietro