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Faster and More Accurate Face Detection on Mobile Robots using Geometric Constraints

Michael Dixon, Frederick Heckel, Robert Pless, and William D. Smart.
In "IEEE/RSJ International Conference on Robots and Systems (IROS 2007)", pages 1041-1046 , 2007.

We develop a framework to allow generic object detection algorithms to exploit geometric information commonly available to robot vision systems. Robot systems take pictures with calibrated cameras from known positions and may simultaneously capture depth measurements in the scene. This allows known constraints on the 3D size and position of objects to be translated into constraints on potential locations and scales of objects in the image, eliminating potentially expensive image operations for geometrically infeasible object locations. We show this integration to be very natural in the context of face detection and find that the computational effort of the standard Viola Jones face detector (as implemented in OpenCV) can be reduced by 85 percent with three times fewer false positives.

Paper: [PDF]

@inproceedings{iros07b,
  author = {Dixon, Michael and Heckel, Frederick and Pless, Robert and Smart, William D.},
  title = {Faster and More Accurate Face Detection on Mobile Robots using Geometric Constraints},
  booktitle = {{IEEE/RSJ} International Conference on Robots and Systems (IROS 2007)},
  pages = {1041--1046 },
  year = {2007}
}