On color-, infrared-, and multimodal-stereo approaches to pedestrian detection
On color-, infrared-, and multimodal-stereo approaches to pedestrian detection
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DOI：
10.1109/tits.2007.908722
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发表时间：
2007-12-01
影响因子：
8.5
通讯作者：
Trivedi, Mohan Manubhai
中科院分区：
文献类型：
--
作者：
Krotosky, Stephen J.;Trivedi, Mohan Manubhai
本文分析了行人检测的彩色、红外和多模态立体方法。我们设计了一个四摄像头实验测试台，由两个彩色摄像头和两个红外摄像头组成，用于捕获和分析行人检测的各种配置排列。我们将这个四摄像头系统集成到测试车辆中，并使用单峰彩色和红外图像进行基于立体的障碍物检测方法的比较实验。对用于将检测到的障碍物分类为行人区域的颜色和红外特征的详细分析用于促进行人检测多模式解决方案的开发。我们提出了一种多模态三焦框架，由一对立体彩色相机和一个红外相机组成。我们使用该框架结合多模态图像特征进行行人检测，并证明当颜色、视差和红外特征一起使用时，检测性能显着提高。这一结果激发了实验和讨论，以使用排列在交叉光谱立体对中的单色和单个红外相机来实现多模态特征组合。我们演示了一种跨模态注册多个对象的方法，并提供了实验分析，强调了采用跨谱方法进行多模态和多视角行人分析的问题和挑战。
This paper presents an analysis of color-, infrared-, and multimodal-stereo approaches to pedestrian detection. We design a four-camera experimental testbed consisting of two color and two infrared cameras for capturing and analyzing various configuration permutations for pedestrian detection. We incorporate this four-camera system in a test vehicle and conduct comparative experiments of stereo-based approaches to obstacle detection using unimodal color and infrared imageries. A detailed analysis of the color and infrared features used to classify detected obstacles into pedestrian regions is used to motivate the development of a multimodal solution to pedestrian detection. We propose a multimodal trifocal framework consisting of a stereo pair of color cameras coupled with an infrared camera. We use this framework to combine multimodal-image features for pedestrian detection and to demonstrate that the detection performance is Significantly higher when color, disparity, and infrared features are used together. This result motivates experiments and discussion toward achieving multimodal-feature combination using a single color and a single infrared camera arranged in a cross-spectral stereo pair. We demonstrate an approach to registering multiple objects across modalities and provide an experimental analysis that highlights issues and challenges of pursuing the cross-spectral approach to multimodal and multiperspective pedestrian analysis.