Extended Feature Descriptor and Vehicle Motion Model with Tracking-by-Detection for Pedestrian Active Safety
Extended Feature Descriptor and Vehicle Motion Model with Tracking-by-Detection for Pedestrian Active Safety
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DOI：
10.1587/transinf.e97.d.296
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发表时间：
2014-02
期刊：
影响因子：
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通讯作者：
Hirokatsu Kataoka;K. Tamura;K. Iwata;Y. Satoh;Y. Matsui;Y. Aoki
中科院分区：
文献类型：
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作者：
Hirokatsu Kataoka;K. Tamura;K. Iwata;Y. Satoh;Y. Matsui;Y. Aoki
在日本，行人在交通事故中的死亡率正在上升。近年来，有人呼吁采取措施保护行人和骑自行车者等易受伤害的道路使用者。在这项研究中，提出了一种方法来检测和跟踪行人使用车载摄像头。我们通过使用单目摄像机获得的高精度图像来改进行人检测技术。在检测步骤中，我们采用ECoHOG作为特征描述符;它累积积分梯度强度。在跟踪步骤中，我们应用一个有效的运动模型，使用光流和建议的特征描述符ECoHOG在跟踪检测框架。使用在真实的道路上捕获的图像对这些技术进行了验证。关键词：行人主动安全，检测跟踪，ECoHOG，粒子滤波，车辆运动模型
The percentage of pedestrian deaths in traffic accidents is on the rise in Japan. In recent years, there have been calls for measures to be introduced to protect vulnerable road users such as pedestrians and cyclists. In this study, a method to detect and track pedestrians using an in-vehicle camera is presented. We improve the technology of detecting pedestrians by using the highly accurate images obtained with a monocular camera. In the detection step, we employ ECoHOG as the feature descriptor; it accumulates the integrated gradient intensities. In the tracking step, we apply an effective motion model using optical flow and the proposed feature descriptor ECoHOG in a tracking-by-detection framework. These techniques were verified using images captured on real roads. key words: Pedestrian Active Safety, Tracking-by-detection, ECoHOG, Particle Filter, Vehicle Motion Model