Abstract
Markerless vision-based human motion analysis has the potential to provide an inexpensive, non-obtrusive solution for the estimation of body poses. The significant research effort in this domain has been motivated by the fact that many application areas, including surveillance, Human-Computer Interaction and automatic annotation, will benefit from a robust solution. In this paper, we discuss the characteristics of human motion analysis. We divide the analysis into a modeling and an estimation phase. Modeling is the construction of the likelihood function, estimation is concerned with finding the most likely pose given the likelihood surface. We discuss model-free approaches separately. This taxonomy allows us to highlight trends in the domain and to point out limitations of the current state of the art.
Original language | Undefined |
---|---|
Article number | 10.1016/j.cviu.2006.10.016 |
Pages (from-to) | 4-18 |
Number of pages | 15 |
Journal | Computer vision and image understanding |
Volume | 108 |
Issue number | LNCS4549/1-2 |
DOIs | |
Publication status | Published - Oct 2007 |
Keywords
- HMI-HF: Human Factors
- HMI-CI: Computational Intelligence
- EWI-11047
- METIS-241905
- IR-61911
- HMI-VRG: Virtual Reality and Graphics
- EC Grant Agreement nr.: FP6/033812