Earticle

초록

영어

Human action recognition has been a widely studied topic in the field of computer. However challenging problems exist for both local and global methods to classify human actions. Local methods usually ignore the structure information among local descriptors. Global methods generally have difficulties in occlusion and background clutter. To solve these problems, a novel combination representation called global Gist feature and local patch coding is proposed. Firstly, Gist feature captures spectrum information of actions in a global view, with spatial relationship among body parts. Secondly, Gist feature located in different grids of the action-centric region is divided into four patches according to the frequencies of action variance. Afterwards on the basis of traditional bag-of-words (BoW) model, a novel formation of local patch coding is adopted. Each patch is encoded independently and finally all the visual words are concatenated to represent high variability of human actions. By combining local patch coding, the proposed method not only solves the problem that global descriptors can not reliably identified actions in complex backgrounds, but also reduces the redundant features in a video. Experimental results performed on KTH and UCF sports dataset demonstrate that the proposed representation is effective for human action recognition.

목차

Abstract
 1. Introduction
 2. The Framework of Proposed Method
 3. Action Recognition with Global Gist Feature and Local Patch Coding
  3.1. Action-centric Region Extraction and Normalization
  3.2. Gist Feature Computation
  3.3. Local Patch Coding
  3.4. Action Recognition
 4. Experiments and Results
  4.1. Experimental Settings
  4.2. Results and Analysis on UCF Sports Dataset
  4.3. Results and Analysis on KTH Dataset
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Yangyang Wang [ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, People’s Republic of China ]
• Yibo Li [ College of Automation, Shenyang Aerospace University, Shenyang 110136, People’s Republic of China ]
• Xiaofei Ji [ College of Automation, Shenyang Aerospace University, Shenyang 110136, People’s Republic of China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605