摘要分别介绍了 Lucas-Kanade 法、Horn-Schunck 法和 Brox 等人的 Warping 法,并使用这三种光流方法计算图像序列的光流场。然后对所得光流图像依次进行灰度化处理、自适应阈值分割、形态学滤波和目标查找,并在图像序列中标识出影响车门开启的移动物体。接着利用两种不同的图像数据集对三种光流方法进行测试评估,分析各方法的优缺点。之后测试了由这三种光流算法计算的光流场用于运动目标获取的情况,分析了三种光流方法对车门开启提示系统性能的影响。最后,针对前面的测试结果对光流算法和运动目标获取系统提出改进建议。9888
关键词 Lucas-Kanade 法,Horn-Schunck 法,Brox 等人的 Warping 法,灰度化
处理,自适应阈值分割,形态学滤波,目标查找
Title Visual perception based car door opening security-reminder system
Abstract
Lucas-Kanade Method, Horn-Schunck Method and Warping Method developed by
Brox etc. are introduced in this article respectively. These methods have
been adopted to compute the optical flow of image sequences. And the
resulted images will be processed by graying, adaptive thresholding
segmentation, morphological filtering and target searching successively.
Moving objects that affect vehicle’s door open will be marked in the image
sequences. We tested these optical flow methods with two different image
datasets and evaluated both their pros and cons. Furthermore, we tested
their performance by using the above mentioned algorithms to search moving
target and analyzed their influence on the visual perception based car door
opening security-reminder system. At last, suggestions have been provided
based on above test results.
Keywords Lucas-Kanade method, Horn-Schunck method, Warping method
developed by Brox etc., graying, adaptive thresholding segmentation,
morphological filtering, target searching
目 次