A Fast and Precise HOG-Adaboost Based Visual Support System Capable to Recognize Pedestrian and Estimate Their Distance
A Fast and Precise HOG-Adaboost Based Visual Support System Capable to Recognize Pedestrian and Estimate Their Distance
复制标题
DOI：
10.1007/978-3-642-41190-8_3
复制
发表时间：
2013-09
期刊：
影响因子：
--
通讯作者：
Kishino Takahisa;Zhe Sun;R. Micheletto
中科院分区：
文献类型：
--
作者：
Kishino Takahisa;Zhe Sun;R. Micheletto
本文提出了一种视觉障碍者的视觉支持系统.我们的检测算法是基于众所周知的方向直方图（HOG）方法，由于其高检测率和通用性[5]。然而，由于较高的误检率，降低了目标识别率的准确性。为了解决这个问题，多部分模型和三相检测已经实现。考虑到变形和平移，这些额外的过滤阶段通过对样品的不同区域的单独作用来进行。结果表明，该方法提高了计算精度和速度。通过基于大数据集的评估实验，我们发现错误检测相对于标准HOG检测器已经改善了18.9%。实验测试还表明，系统能够通过使用简单的透视模型来估计行人的距离。该系统已在几个摄影数据集上进行了测试，并在模糊的情况下也表现出出色的性能。
In this paper,we present a visual support system the visually impaired. Our detection algorithm is based on the well known Histograms of Oriented Gradients (HOG) method, due to its high detection rate and versatility [5]. However, the accuracy of object recognition rate is reduced because of high false detection rate. In order to solve that, multiple parts model and triple phase detection have been implemented. These additional filtering stages were conducted by separate action on different area of the sample, considering deformations and translations. We demonstrated that this approach has raised the accuracy and speed of calculation. Through an evaluation experiment based on a large dataset, we found that false detection has been improved by 18.9% in respect to standard HOG detectors. Experimental tests have also shown the system ability to estimate the distance of the pedestrian by the use of a simple perspective model. The system has been tested on several photographic datasets and have shown excellent performances also in ambiguous cases.