Study of face recognition technology based on STASM and its application in video retrieval

被引：0
作者：
Liu, Chunlei [1 ]
Chen, Kun [1 ]
Xu, Yongjin [1 ]
机构：
[1] Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai Key Laboratory of Power Station Automation Technology, Shanghai
来源：
Communications in Computer and Information Science | 2014年 / 462卷
关键词：
Face detection; Face recognition; STASM; Video retrieval;
D O I：
10.1007/978-3-662-45261-5_23
中图分类号：
学科分类号：
摘要：
The gradual perfection of video retrieval technology has a positive effect in maintaining public order. However, with the improving complexity of monitoring environment, the increase of related video data requires further improvement to the efficiency of video retrieval technology. Video retrieval technology aiming at processing massive video data is needed urgently and it has become hot research subject in multimedia retrieval area. In this paper, the application of face recognition technology in video retrieval is discussed. To improve the retrieval efficiency, STASM algorithm based on OpenCV software platform is designed. The research involves the acquisition of video image frame data, face recognition and detection. Experimental results demonstrate the effectiveness and efficiency of the algorithms. © Springer-Verlag Berlin Heidelberg 2014.
引用
收藏
页码：219 / 227
页数：8
相关论文
共 7 条
  • [1] Tan H.C., Zhang Y.J., Computing Eigenface from Edge Images for Face Recognition Based on Hausdorff Distance, Proceedings of the 4Th International Conference on Image and Graphics, (2007)
  • [2] Barkan O., Weill J., Wolf L., Aronowitz H., Fast high dimensional vector multiplication face recognition, ICCV, (2013)
  • [3] Simonyan K., Parkhi O.M., Vedaldi A., Zisserman A., Fisher vector faces in the wild, BMVC, (2013)
  • [4] Li H., Hua G., Lin Z., Brandt J., Yang J., Probabilistic elastic matching for pose variant face verification, CVPR, (2013)
  • [5] Cootes T.F., Edwards G., Taylor C.J., Comparing Active Shape Models with Active Appearance Models, Proceedings of British Machine Vision Conference, (1999)
  • [6] Kong J., Han C., Content-based video retrieval system research, IEEE Conference on Computer Science and Information Technology, (2010)
  • [7] Smeulders, Worring M., Santini S., Content-based image retrieval at the end of the early years, EEE Trans. Pattern Anal. Machine Intel, (2000)
1