Object Recognition Based on n-gram Expression of Human Actions
Object Recognition Based on n-gram Expression of Human Actions
复制标题
DOI：
10.1109/icpr.2010.99
复制
发表时间：
2010-08
期刊：
影响因子：
--
通讯作者：
A. Kojima;H. Miki;K. Kise
中科院分区：
文献类型：
--
作者：
A. Kojima;H. Miki;K. Kise
在本文中，我们提出了一种新的方法来识别对象，通过观察人的行为的基础上袋的功能。我们的方法的主要贡献是，人类的行动表示为符号的n-gram，并用于识别特定的对象类别。首先，从视频图像中提取人对物体的动作特征，并将其编码为符号。然后，从符号序列生成n元语法，并针对相应的对象类别进行注册。对于识别阶段，对对象采取的动作以相同的方式转换成一组n-gram，并与表示对象类别的动作进行比较。我们进行了实验，以识别对象在办公室环境中，并证实了我们的方法的有效性。
In this paper, we propose a novel method for recognizing objects by observing human actions based on bag-of-features. The key contribution of our method is that human actions are represented as n-grams of symbols and used to identify specific object categories. First, features of human actions taken on a object are extracted from video images and encoded to symbols. Then, n-grams are generated from the sequence of symbols and registered for corresponding object category. For recognition phase, actions taken on the object are converted into set of n-grams in the same way and compared with ones representing object categories. We performed experiments to recognize objects in an office environment and confirmed the effectiveness of our method.