Body Tracking from Single-Camera Video
We have developed a method to reconstruct the 3-d positions of a moving human figure from observing the figure's motions over time, recorded from a single video camera. This may have application to human-computer interaction, computer graphics, or interative virtual environments. Reconstructing 3-d from 2-d (image) information is an under-determined problem, and we must rely of prior knowledge about how people tend to move in order to resolve ambiguities.
Background & Objective: As one watches a film or video of a person moving, one can easily estimate the 3-dimensional motions of the moving person from watching the 2-d projected images over time. A dancer could repeat the motions depicted in the film. Yet such 3-d motion is hard for a computer to estimate. Such estimation is the goal of this work.
Technical Discussion: Our approach is to use strong prior knowledge about how humans move. We show that this prior knowledge dramatically improves the 3d reconstructions. We learn our prior model from examples of 3-d human motion. Those results show how to estimate the 3-d figure motion if we can place a 2-d stick figure over the image of the moving person. We developed such a tracker, allowing interactive correction of tracking mistakes, to test our 3-d recovery method. We show good recovery of 3-d motion for a difficult dance sequence, viewed from a single camera. These results show the power of adding prior knowledge about human motions, in a Bayesian framework, to the problem of interpreting images of people.
| Technical Reports: | |
| Bayesian Estimation of 3-D Human Motion | |
Technology Areas:
Computer Vision
Graphics
Modification Date: September 12, 2007