CAJ | 학술논문

文章主要研究基于视频的行为识别技术。该技术主要用于识别时空混合的视频数据中的人类行为活动，它不同于二维图像识别技术和三维时空兴趣点检测方法。主要讨论如何通过提取立方体像素窗口、聚类生成特征字典完成识别工作。文章所使用的方法主要包括离散线性过滤器的实现和关键参数的选择、对K-means聚类算法的改进、分类器设计等。通过在公开数据库上的实验，表明文章使用的方法是有效的，取得了比较理想的结果。
문장주요연구기우시빈적행위식별기술。해기술주요용우식별시공혼합적시빈수거중적인류행위활동，타불동우이유도상식별기술화삼유시공흥취점검측방법。주요토론여하통과제취립방체상소창구、취류생성특정자전완성식별공작。문장소사용적방법주요포괄리산선성과려기적실현화관건삼수적선택、대K-means취류산법적개진、분류기설계등。통과재공개수거고상적실험，표명문장사용적방법시유효적，취득료비교이상적결과。
This paper focuses on the behavior recognition technology video. The technology is mainly used for activities of human behavior recognition time video data in hybrid, which is different from the two-dimensional image recognition technology and 3D spatio-temporal interest point detection method. Mainly discuss how to extract the cube pixel window, clustering feature dictionary complete identiifcation. The method used by the authors mainly includes the implementation and key parameters of discrete linear iflter selection, improvement of K-means clustering algorithm, the design of classiifer. Through the open database experiments, show that this method is effective, and the ideal results are achieved.