Carnegie Mellon University
Human Face Detection in Visual Scenes

Henry Rowley, Shumeet Baluja, and Takeo Kanade
Advances in Neural Information Processing Systems 8, 1996, pp. 875 - 881.

  • Adobe portable document format (pdf) (698KB)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

We present a neural network-based face detection system. A retinally connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We use a bootstrap algorithm for training, which adds false detections into the training set as training progresses. This eliminates the difficult task of manually selecting non-face training examples, which must be chosen to span the entire space of non-face images. Comparisons with another state-of-the-art face detection system are presented; our system has better performance in terms of detection and false-positive rates.

Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): Face Group
Associated Project(s): Neural Network-Based Face Detection, Face Detection Databases, Face Detection, Face Databases

Text Reference
Henry Rowley, Shumeet Baluja, and Takeo Kanade, "Human Face Detection in Visual Scenes," Advances in Neural Information Processing Systems 8, 1996, pp. 875 - 881.

BibTeX Reference
   author = "Henry Rowley and Shumeet Baluja and Takeo Kanade",
   title = "Human Face Detection in Visual Scenes",
   booktitle = "Advances in Neural Information Processing Systems 8",
   pages = "875 - 881",
   year = "1996",