用于进行人脸口罩识别的XML.zip

<?xml version="1.0"?> <!-- 18x15 Nose detector computed with 7000 positive samples ////////////////////////////////////////////////////////////////////////// | Contributors License Agreement | IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. | By downloading, copying, installing or using the software you agree | to this license. | If you do not agree to this license, do not download, install, | copy or use the software. | | Copyright (c) 2008, Modesto Castrillon-Santana (IUSIANI, University of | Las Palmas de Gran Canaria, Spain). | All rights reserved. | | Redistribution and use in source and binary forms, with or without | modification, are permitted provided that the following conditions are | met: | | * Redistributions of source code must retain the above copyright | notice, this list of conditions and the following disclaimer. | * Redistributions in binary form must reproduce the above | copyright notice, this list of conditions and the following | disclaimer in the documentation and/or other materials provided | with the distribution. | * The name of Contributor may not used to endorse or promote products | derived from this software without specific prior written permission. | | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE | CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, | EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, | PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR | PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF | LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING | NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Back to | Top ////////////////////////////////////////////////////////////////////////// RESEARCH USE: If you are using any of the detectors or involved ideas please cite one of these papers: @ARTICLE{Castrillon07-jvci, author = "Castrill\'on Santana, M. and D\'eniz Su\'arez, O. and Hern\'andez Tejera, M. and Guerra Artal, C.", title = "ENCARA2: Real-time Detection of Multiple Faces at Different Resolutions in Video Streams", journal = "Journal of Visual Communication and Image Representation", year = "2007", vol = "18", issue = "2", month = "April", pages = "130-140" } @INPROCEEDINGS{Castrillon07-swb, author = "Castrill\'on Santana, M. and D\'eniz Su\'arez, O. and Hern\'andez Sosa, D. and Lorenzo Navarro, J. ", title = "Using Incremental Principal Component Analysis to Learn a Gender Classifier Automatically", booktitle = "1st Spanish Workshop on Biometrics", year = "2007", month = "June", address = "Girona, Spain", file = F } A comparison of this and other face related classifiers can be found in: @InProceedings{Castrillon08a-visapp, 'athor = "Modesto Castrill\'on-Santana and O. D\'eniz-Su\'arez, L. Ant\'on-Canal\'{\i}s and J. Lorenzo-Navarro", title = "Face and Facial Feature Detection Evaluation" booktitle = "Third International Conference on Computer Vision Theory and Applications, VISAPP08" year = "2008", month = "January" } More information can be found at http://mozart.dis.ulpgc.es/Gias/modesto_eng.html or in the papers. COMMERCIAL USE: If you have any commercial interest in this work please contact mcastrillon@iusiani.ulpgc.es --> <opencv_storage> <classifier_Nariz_20stages type_id="opencv-haar-classifier"> <size> 18 15</size> <stages> <_> <!-- stage 0 --> <trees> <_> <!-- tree 0 --> <_> <!-- root node --> <feature> <rects> <_> 8 4 4 4 -1.</_> <_> 8 4 4 2 2.</_></rects> <tilted>1</tilted></feature> <threshold>0.0363217890262604</threshold> <left_val>-0.6772649884223938</left_val> <right_val>0.6687346100807190</right_val></_></_> <_> <!-- tree 1 --> <_> <!-- root node --> <feature> <rects> <_> 3 0 12 7 -1.</_> <_> 6 0 6 7 2.</_></rects> <tilted>0</tilted></feature> <threshold>0.0544859282672405</threshold> <left_val>-0.4403176903724670</left_val> <right_val>0.4891850948333740</right_val></_></_> <_> <!-- tree 2 --> <_> <!-- root node --> <feature> <rects> <_> 3 5 12 9 -1.</_> <_> 3 8 12 3 3.</_></rects> <tilted>0</tilted></feature> <threshold>-0.1508972942829132</threshold> <left_val>0.6370239257812500</left_val> <right_val>-0.2814675867557526</right_val></_></_> <_> <!-- tree 3 --> <_> <!-- root node --> <feature> <rects> <_> 6 0 6 8 -1.</_> <_> 6 0 3 8 2.</_></rects> <tilted>0</tilted></feature> <threshold>-0.0794939175248146</threshold> <left_val>0.6347042918205261</left_val> <right_val>-0.1611918956041336</right_val></_></_> <_> <!-- tree 4 --> <_> <!-- root node --> <feature> <rects> <_> 3 8 12 4 -1.</_> <_> 3 10 12 2 2.</_></rects> <tilted>0</tilted></feature> <threshold>-0.0670417398214340</threshold> <left_val>0.5956599712371826</left_val> <right_val>-0.1645421981811523</right_val></_></_> <_> <!-- tree 5 --> <_> <!-- root node --> <feature> <rects> <_> 10 1 3 8 -1.</_> <_> 10 1 3 4 2.</_></rects> <tilted>1</tilted></feature> <threshold>0.1654247045516968</threshold> <left_val>-0.0291650108993053</left_val> <right_val>0.2784962058067322</right_val></_></_> <_> <!-- tree 6 --> <_> <!-- root node --> <feature> <rects> <_> 8 1 8 3 -1.</_> <_> 8 1 4 3 2.</_></rects> <tilted>1</tilted></feature> <threshold>0.1449110060930252</threshold> <left_val>-0.1593054980039597</left_val> <right_val>0.5626019239425659</right_val></_></_> <_> <!-- tree 7 --> <_> <!-- root node --> <feature> <rects> <_> 3 0 12 3 -1.</_> <_> 3 1 12 1 3.</_></rects> <tilted>0</tilted></feature> <threshold>-0.0126969404518604</threshold> <left_val>-0.6924440860748291</left_val> <right_val>0.1042767018079758</right_val></_></_> <_> <!-- tree 8 --> <_> <!-- root node --> <feature> <rects> <_> 8 0 2 3 -1.</_> <_> 8 1 2 1 3.</_></rects> <tilted>0</tilted></feature> <threshold>5.2858339622616768e-003</threshold> <left_val>0.0736001133918762</left_val> <right_val>-0.8135973