Combining Skin-Color Detector and Evidence Aggregated Random Field Models Towards Validating Face Detection Results

Publication Type:

Conference Paper


S. Krishna, S. Panchanathan


Sixth Indian Conference on Computer Vision, Graphics and Image Processing (2008)


In this paper, a framework for validating any generic face detection algorithm’s result is proposed. A two stage cascaded face validation filter is described that relies on a skin-color detector and on a face silhouette structure modeler towards increasing face detection capacity of any face detection algorithm. While the skin-color detector combines a static skin-color and a dynamic background-color modeler, the face silhouette structure modeler incorporates an aggregate of random field models combined through a Demspter-Shafer framework of evidence merging. Together, the two modelers validate any face subimage generated by face detection algorithms. Experiments conducted on FERET and on an in-house face database supports the claimfor improved face detection results using the proposed filter. An extension of the same framework towards head pose estimation is also suggested.


Sreekar Krishna

Sreekar Krishna

Assistant Research Technologist

Dr. Sethuraman "Panch" Panchanathan

Dr. Sethuraman "Panch" Panchanathan

Director, National Science Foundation