Our algorithm can detect between 78.9% and 90.5% of faces in a set of 130 total images, with an acceptable number of false detections. Depending on the application, the system can be made more or less conservative by varying the arbitration heuristics or thresholds used. The system has been tested on a wide variety of images, with many faces and unconstrained backgrounds.
There are a number of directions for future work. The main limitation of the current system is that it only detects upright faces looking at the camera. Separate versions of the system could be trained for each head orientation, and the results could be combined using arbitration methods similar to those presented here. It would also be interesting to apply this method to detecting other objects.
Even within the domain of detecting frontal views of faces, more work remains. When an image sequence is available, temporal coherence can focus attention on particular portions of the images. As a face moves about, its location in one frame is a strong predictor of its location in next frame. Standard tracking methods, as well as expectation-based methods , can be applied to focus the detector's attention.
Other methods of improving system performance include obtaining more positive examples for training, or applying more sophisticated image preprocessing and normalization techniques. For instance, the color segmentation method used in  for color-based face tracking could be used to filter images. The face detector would then be applied only to portions of the image which contain skin color, which would speed up the algorithm as well as eliminating false detections.
One application of this work is in the area of media technology. Every year, improved technology provides cheaper and more efficient ways of storing information. However, automatic high-level classification of the information content is very limited; this is a bottleneck that prevents media technology from reaching its full potential. The work described above allows a user to make queries of the form ``Which scenes in this video contain human faces?'' and to have the query answered automatically.