Efficiently learning a detection cascade with sparse eigenvectors
Real-time object detection has many computer vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detection system, much effort has been spent on improving the boosting method. In this work, we first show that feature selection methods other than boosting can also be used for training an efficient object detector. In particular, we introduce greedy sparse linear discriminant analysis (GSLDA) for its conceptual simplicity and computational efficiency; and...[Show more]
|Collections||ANU Research Publications|
|Source:||IEEE Transactions on Image Processing|
|01_Shen_Efficiently_learning_a_2011.pdf||2.5 MB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.