基于LBP纹理和改进Camshift算子的车辆检测与跟踪

提出了利用背景图像LBP（局部二值模式）纹理和当前帧图像LBP纹理的相似度分析提取前景的方法，克服了车辆检测中常用的帧差法、背景差分法对光照比较敏感的缺点.同时基于H,S,V分量及改进的LBP纹理的联合直方图与金字塔L-K光流法中心跟踪相结合的Camshift跟踪算法，有效地解决了背景目标颜色相近可能会导致跟踪的目标区域加入背景后变大、处理较大帧间位移的视频跟踪上搜索窗口的位置准确度较低的问题.实验证明，该方法具有良好的检测和追踪效果.

Vehicle Detection and Tracking Based on the Local Binary Pattern Texture and Improved Camshift Operator

A method of extraction prospect, which uses the background image LBP (local binary pattern) texture and current frame image LBP texture similarity analysis, was put forward. This method overcomes the sensitivity to illumination methods in vehicle detection, such as frame difference method and background difference method. The Camshift tracking algorithm combines the H,S and V components, the improved LBP texture of the joint histogram with the centroid tracking by pyramid L-K optical flow. This method can effectively solve two problems: one that the similar background color may lead to the tracking of the target area bigger, and the other that the search window position accuracy is low when dealing with large displacement between frames of video. The experimental results prove that the method has good detection and tracking effect.