Detection of Multiple Humans Using Motion Information and Adaboost Algorithm based on Harr-like Features
Detection of Multiple Humans Using Motion Information and Adaboost Algorithm based on Harr-like Features
复制标题
DOI：
--
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
J. Lim;Wookhyun Kim
中科院分区：
文献类型：
--
作者：
J. Lim;Wookhyun Kim
对图像序列中的人体进行稳健检测对于许多应用都很重要。然而，如果人类彼此相邻，那么要准确地检测到他们就困难得多。在本文中，我们提出了一种在移动或固定系统上利用运动信息和Adaboost算法从单个摄像机自动检测多人的方法。在移动系统的情况下，摄像机的自我运动被相应的特征集补偿。通过使用补偿了自我运动的两个连续图像之间的差图像的投影方法来搜索运动对象可能存在的感兴趣区域。人类检测器是通过增强一些基于类Harr特征的弱分类器来学习的。该方法已经在多个图像序列上进行了测试，并被证明能很好地检测出多个人。
Robust detection of humans in image sequences is important for many applications. However, if humans are adjacent to each other, it is much more difficult to accurately detect them. In this paper, we propose a method to automatically detect multiple humans using motion information and Adaboost algorithm from a single camera on a mobile or stationary system. In case of mobile system, the ego-motion of the camera is compensated by the corresponding feature sets. The region of interest that moving objects are likely to exist is searched by the projection approach using a difference image between two consecutive images that an ego-motion is compensated. Human detector is learned by boosting a number of weak classifiers which are based on Harr-like features. The proposed approach has been tested to a number of image sequences, and it was shown to detect multiple humans very well.