Human motion recognition with a convolution kernel

Dongwei Cao, Osama T. Masoud, Daniel L Boley

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We address the problem of human motion recognition in this paper. The goal of human motion recognition is to recognize the type of motion recorded in a video clip, which consists of a set of temporarily ordered frames. By defining a Mercer kernel between two video clips directly, we propose in this paper a recognition strategy that can incorporate both the information of each individual frame and the temporal ordering between frames. Combining the proposed kernel with the support vector machine, which is one of the most effective classification paradigms, the resulting recognition strategy exhibits excellent performance over real data sets.

Original languageEnglish (US)
Title of host publicationProceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006
Pages4270-4275
Number of pages6
DOIs
StatePublished - 2006
Event2006 IEEE International Conference on Robotics and Automation, ICRA 2006 - Orlando, FL, United States
Duration: May 15 2006May 19 2006

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2006
ISSN (Print)1050-4729

Other

Other2006 IEEE International Conference on Robotics and Automation, ICRA 2006
CountryUnited States
CityOrlando, FL
Period5/15/065/19/06

Keywords

  • Convolution kernels
  • Human motion recognition
  • Support vector machines

Fingerprint Dive into the research topics of 'Human motion recognition with a convolution kernel'. Together they form a unique fingerprint.

Cite this