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RI | Research | Projects | Neural Network-Based Face Detection
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Neural Network-Based Face Detection This project is no longer active.
Head: Takeo Kanade
Mailing address:
Associated center: VASC For more information, see this project's homepage.
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| Project Description |
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 the networks, 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 other state-of-the-art face detection systems are presented; our system has better performance in terms of detection and false-positive rates.
| Past members |
| Name | Title | Email Address | |
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Shumeet Baluja | Adjunct Faculty (Adjunct) | baluja@cs.cmu.edu |
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Takeo Kanade | U.A. and Helen Whitaker University Prof., RI/CS | tk@cs.cmu.edu |
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Henry Rowley | PhD Student, CS |
| Recent publications [View all 11 publications] |