Estimating the physical effort of human poses

Yinpeng Chen, Hari Sundaram, Jodi James

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


This paper deals with the problem of estimating the effort required to maintain a static pose by human beings. The problem is important in developing effective pose classification as wells as in developing models of human attention. We estimate the human pose effort using two kinds of body constraints - skeletal constraints and gravitational constraints. The extracted features are combined together using SVM regression to estimate the pose effort. We tested our algorithm on 55 poses with different annotated efforts with excellent results. Our user studies additionally validate our approach.

Original languageEnglish (US)
Title of host publicationImage and Video Retrieval - 5th International Conference, CIVR 2006, Proceedings
Number of pages4
ISBN (Print)3540360182, 9783540360186
StatePublished - 2006
Externally publishedYes
Event5th International Conference on Image and Video Retrieval, CIVR 2006 - Tempe, AZ, United States
Duration: Jul 13 2006Jul 15 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4071 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th International Conference on Image and Video Retrieval, CIVR 2006
Country/TerritoryUnited States
CityTempe, AZ

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Estimating the physical effort of human poses'. Together they form a unique fingerprint.

Cite this