Abstract
Human motion analysis is a challenging research area aimed at automating the study of human behavior. An important part of any such system is the component that performs the Human Motion Capture (HMC); in order for human motion to be processed and semantically analyzed, a mathematical representation of the observed motion needs to be extracted. There are two separate aspects to a HMC system; sensing (hardware) and processing (software). The processing itself comprises of an initialization (anthropometry and pose estimation) and a tracking phase. In this chapter, we present methods for three-dimensional model-based human motion capture from uncalibrated passive optical sensors with semi-antomatic initialization and tracking. Such methods allow for non-untrusive capture of natural human behavior from video cameras or from archival recordings. We demonstrate the accuracy, advantages, and limitations of our methods for various classes of data.
Original language | English (US) |
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Title of host publication | Handbook of Mathematical Models in Computer Vision |
Publisher | Springer US |
Pages | 325-340 |
Number of pages | 16 |
ISBN (Print) | 0387263713, 9780387263717 |
DOIs | |
State | Published - 2006 |
ASJC Scopus subject areas
- Computer Science(all)