A Tracking Framework for Accurate Face Localization
Achieving a good localization of faces on video frames is of high importance for an application such as video indexing. Face localization on movies is an ambiguous task due to various scale, pose and lighting conditions.
A novel deterministic approach has been developed that it applies face detection, forward tracking and backward tracking, using some predefined rules. From all the possible extracted candidates, a Dynamic Programming algorithm selects those that minimize a cost function.
Use of the Haar-like features to provide first face candidates. For tracking purposes, a post-processing step is added to reduce the number of false alarms and remove some of the background. Candidates are rejected if the number of pixels fulfilling the criteria below are under a certain threshold.
0 < h < 1 and 0.23 < s < 0.68 and 0.27 < v
The remaining candidates are replaced by the smallest bounding box containing the skin-like pixels. The detection is performed every 5 frames.
Forward tracking process:
Backward tracking process:
Structure of the trellis
I. Cherif, V. Solachidis and I. Pitas, "A Tracking Framework for Accurate Face Localization", in Proc. of Int. Federation for Information Processing Conf. on Artificial Intelligence (IFIP AI 2006), Santiago, Chile, 21-24 August, 2006.
NM2 - “New media for a new millennium” (IST-004124), FP6