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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Siddiqui, M. Medioni, G. |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. of Southern California, Los Angeles (Siddiqui, M.; Medioni, G.) |
| Abstract | Models that can efficiently, compactly, and semantically represent potential users are important tools for human-robot interaction applications. We model a person as a projection of a generic 3D articulated model and propose a method to estimate its joint positions from image data in an optimization framework. This is done by constructing a function that grades a configuration of joints according to how well it matches the underlying image and model based priors. We then search for local optimum in this space both efficiently and exhaustively by assembling partial configurations in a bottom-up manner. Working from the leaves of the tree to its root, we maintain a list of locally optimal, yet sufficiently distinct candidate configurations for the body pose. We then adapt this algorithm for use on a sequence of images to make it even more efficient by considering configurations that are near their position in the previous frame. This way, the number of partial configurations generated and evaluated significantly reduces. These algorithms are validated on real image data. |
| Starting Page | 678 |
| Ending Page | 683 |
| File Size | 2826304 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424416349 |
| DOI | 10.1109/ROMAN.2007.4415172 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-26 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Robot sensing systems Robot vision systems Cameras Intelligent robots Intelligent sensors Intelligent networks Home automation Sensor arrays Human robot interaction Fitting |
| Content Type | Text |
| Resource Type | Article |
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