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中文摘要：
本文利用智能手机对视频信息进行实时处理,从而实现对前车的检测和车距的估算。采用两步前车检测技术,即寻找车辆假设区域和验证车辆假设区域。通过基于车道先验的两步阈值法提取车底阴影,通过车道先验对阴影进行筛选从而确定车辆假设区域,并利用基于Haar-like特征的Adaboost方法来对车辆假设区域进行验证,之后通过视频流特征对误检信息进行剔除并对车辆进行实时跟踪。本文还结合摄像头透视几何关系,只需用户提供摄像头高度信息即可对前车距离进行准确估算,可以作为有效的危险预警手段。
英文摘要：
In this paper,we use smart phone to process the video in real-time for vehicle detection and distance measurement. Two steps of vehicle detection method is being applied,which are finding hypothesis region and verification of the region. The method uses two steps of extracting the threshold of vehicle shadows based on lane prior,screens out the good shadows in view of lane prior and verifies the shadow by using Adaboost classifier based on Haar-like features. Then the video streaming information is being used for rejecting the non-vehicle region and tracking the vehicle. Perspective geometry is being used for distance measurement during that all a user need to provide is the height of the camera,which can be applied to early warning for risk.
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Hyperspectral Image Classification Based on Structured Sparse Logistic Regression and Three-Dimensio
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