Vector boosting for rotation invariant multi-view face detection
- 1 January 2005
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, 446-453 Vol. 1
- https://doi.org/10.1109/iccv.2005.246
Abstract
In this paper, we propose a novel tree-structured multiview face detector (MVFD), which adopts the coarse-to-fine strategy to divide the entire face space into smaller and smaller subspaces. For this purpose, a newly extended boosting algorithm named vector boosting is developed to train the predictors for the branching nodes of the tree that have multicomponents outputs as vectors. Our MVFD covers a large range of the face space, say, +/-45/spl deg/ rotation in plane (RIP) and +/-90/spl deg/ rotation off plane (ROP), and achieves high accuracy and amazing speed (about 40 ms per frame on a 320 /spl times/ 240 video sequence) compared with previous published works. As a result, by simply rotating the detector 90/spl deg/, 180/spl deg/ and 270/spl deg/, a rotation invariant (360/spl deg/ RIP) MVFD is implemented that achieves real time performance (11 fps on a 320 /spl times/ 240 video sequence) with high accuracy.Keywords
This publication has 3 references indexed in Scilit:
- Rapid object detection using a boosted cascade of simple featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Improved Boosting Algorithms Using Confidence-rated PredictionsMachine Learning, 1999
- Boosting the margin: a new explanation for the effectiveness of voting methodsThe Annals of Statistics, 1998