Tracking Loose-limbed People

DMCA

Tracking Loose-limbed People (2004)

Cached

Download Links

Other Repositories/Bibliography

DBLP

by Leonid Sigal , Sidharth Bhatia , Stefan Roth , Michael J. Black , Michael Isard

Citations:

191 - 7 self

BibTeX

@MISC{Sigal04trackingloose-limbed,
    author = {Leonid Sigal and Sidharth Bhatia and Stefan Roth and Michael J. Black and Michael Isard},
    title = {Tracking Loose-limbed People},
    year = {2004}
}

OpenURL

Abstract

We pose the problem of 3D human tracking as one of inference in a graphical model. Unlike traditional kinematic tree representations, our model of the body is a collection of loosely-connected limbs. Conditional probabilities relating the 3D pose of connected limbs are learned from motioncaptured training data. Similarly, we learn probabilistic models for the temporal evolution of each limb (forward and backward in time). Human pose and motion estimation is then solved with non-parametric belief propagation using a variation of particle filtering that can be applied over a general loopy graph. The loose-limbed model and decentralized graph structure facilitate the use of low-level visual cues. We adopt simple limb and head detectors to provide "bottom-up" information that is incorporated into the inference process at every time-step; these detectors permit automatic initialization and aid recovery from transient tracking failures. We illustrate the method by automatically tracking a walking person in video imagery using four calibrated cameras. Our experimental apparatus includes a marker-based motion capture system aligned with the coordinate frame of the calibrated cameras with which we quantitatively evaluate the accuracy of our 3D person tracker.

Keyphrases

loose-limbed people calibrated camera low-level visual cue loosely-connected limb automatic initialization coordinate frame loose-limbed model temporal evolution person tracker conditional probability motioncaptured training data bottom-up information graph structure marker-based motion capture system traditional kinematic tree representation video imagery simple limb aid recovery inference process head detector experimental apparatus probabilistic model non-parametric belief propagation graphical model general loopy graph motion estimation

DMCA