Earticle

초록

영어

To utilize the geometry structure information and similarity information within the neighborhood surrounding a spatio-temporal interest point for human action recognition task, we employ the axes of a regular polyhedron as a reference locating system, and build a novel local feature named polyhedron neighborhood feature (PNF). Then, to reduce quantization error in the coding stage, locality-constrained linear coding method is used to encode the obtained PNFs. Next, multi-temporal-scale PNFs (MPNFs) are created for handling the problem of various action speeds. In classification, support vector machine (SVM) based on linear kernel is used as classifier taking time consumption into account. The experiments on the KTH and UCF sports datasets show that the recognition system based on PNFs achieves better performance than the competing local spatio-temporal feature-based human action recognition methods.

목차

Abstract
 1. Introduction
 2. Building Polyhedron Neighborhood Features
  2.1. Detecting Spatio-temporal Interest Points (STIPs)
  2.2. Employing the Axes of Regular Polyhedron as Position Locating System
  2.3. Building Polyhedron Neighborhood Feature
 3. Encoding PNFs by LLC
  3.1. Vector Quantization and Sparse Coding
  3.2. Locality-constrained Linear Coding (LLC)
 4. Building Multi-temporal-scale PNFs (MPNFs)
 5. Experiment and Analysis
  5.1. Experiment Setup
  5.2. Datasets
  5.3. Experimental Result and Analysis
 6. Conclusion
 Acknowledgement
 References

키워드

저자

• Jiangfeng Yang [ School of Communication and Information Engineering University of Electronic Science and Technology of China, Xiyuan Ave, No.2006, West Hi-Tech Zone, 61173 ]
• Zheng Ma [ School of Communication and Information Engineering University of Electronic Science and Technology of China, Xiyuan Ave, No.2006, West Hi-Tech Zone, 61173 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605