摘要
传统的多尺度特征计算都是首先构造不同尺度的图像形成图像金字塔,然后在金字塔每一层上通过滑动窗口的办法提取相应的特征,实验表明在目标检测时特征提取消耗大量时间,改善特征提取的速度是提升目标检测速度的关键。本文使用FFC(Fast Feature Computation)计算方法对多尺度图像特征进行快速提取,同时结合Adaboost算法和多特征融合方法用于行人目标检测,实验结果表明效果较好。
Traditional multi-scale feature extraction method for pedestrian detection firstly constructs image pyramid and then extracts corresponding features by sliding window method. The experiment reflects that it costs much time on feature extraction while we detect pedestrians. What we have to do is improving feature computation speed while does not matter detection perfor-mance. This paper proposes FFC（Fast Feature Computation） method for feature extraction and makes use of Adaboost algorithm and multi-features merge. Experimental results show that the effect is better.
出处
《电脑与电信》
2015年第4期50-52,65,共4页
Computer & Telecommunication
