如何将SURF算法与粒子滤波器跟踪相结合？ [英] How do I integrate SURF algorithm with particle filter tracking?

问题描述

我是图像处理领域的新手。我目前正在尝试使用SURF算法检测视频中的多个人，并使用SVM训练进行检测，并使用粒子滤波器进行跟踪。到目前为止，我使用功能包从一组图像（对于人和非人）构建词汇表和群集关键点，并使用两个SVM来分类测试数据是否是人。现在分类已经完成，我打算使用从测试数据中提取的SURF关键点进行粒子滤波。



基本上，我想证明SURF的合理性适合粒子滤波器输入的关键点，将这些点馈入粒子滤波算法，然后开始跟踪目标并同时绘制代表粒子的圆圈。



我该怎么做呢？ :(我正在尝试研究这里提供的代码 https://github.com/NewProggie/Particle-Filter [ ^ ]但我有点迷路，因为它是AdaBoost，当然，粒子是随机生成的。非常感谢！

I'm new to the image processing field. I'm currently trying to detect multiple persons in a video using the SURF algorithm with SVM training for detection, and the particle filter for tracking. So far, I used the bag-of-features to build a vocabulary and cluster keypoints from a set of images (for both persons and nonpersons) and used two SVMs to classify if the test data are persons or not. Now that the classification is done, I'm planning to use the SURF keypoints extracted from the test data for the particle filter.

Basically, I want to justify the SURF keypoints to suit the particle filter input, feed these points into the particle filter algorithm, and then start tracking the targets and drawing circles representing the particles at the same time.

How do I do this? :( I'm trying to study the code provided here https://github.com/NewProggie/Particle-Filter[^] but I kinda got lost because it AdaBoost, and of course, the particles are generated randomly. Thank you very much!

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