2019年最新-FaceDetectionEE368FinalProject人臉檢測方法ee368最終的項目

1、Face Detection EE368 Final Project Stanford University, Dept, of EETaesang Yoo, Youngjae Kim(Group 7)Algorithm Outline960x1280x3240x320x3240x320x1ResizeDetectSkin-colorsImageSegmentationYesDecision based onratios, sizesEigen face methodNoEdge-BasedPreprocessingSkin colors? Fortunately, skin-colors f

2、orm a cluster in YCbCr color space-Thus, we can approximate the skin color region with several lines.Image segmentationSegmentation based on connected areas9 many face can didate rectangles9put strict restrictions on them 9 face!Eigen face method (1) Applied to suspicious rectanglese.g. a cluster of

3、 faces or non-face rectangles洋臀彗豔33J謂莎聖霜 旨旳MT逮罵站3孚ada 3駕霄也怎3駕鑿 -律ISMIR雲讀lrFsa 番彗-3F3空常!ly帀1彩 黑雪3=3倉羽 M Haaa :<7|空11闆all闇 31音 1丁311龍-1售闊左0 H3IRsllllq3 空 333133 5333 豈凸勺爭丁也0 W13諾JSSuspicious rectanglesFace samples (16x16 pixels)912 eigen facesEigen face method (2)-Detectable range : 21x21 80x80 pix

4、els2-Resizing step: 0.02 (5.00, 4.98, 4.96 .1.30)Detection exampleOriginalReconstructedMiscella ny Hvalue of skin color is less than 0.1 or greater than 0.9 ? (Trials and errors, but useful to remove the background)-Edge based preprocessing speeds up the process by enabling the eigenface method to s

5、kip blank regionsDetection resultTraining_1 JpgCon clusi ons A combination of skin color method & eigenfacemethod Reduced the false alarm rate using two filters Out of 163 faces in the 7 training images, 90% with false alarm rate 5% was detected Dependent on the training set by assumptions made

6、from it (e.g. image size, # of faces, colors)Refere nces-Skin color detectionFace Detection in Color Images using Wavelet Packet Analysis, C. Garcia, G. Zikos, G Tziritas, Institute of Computer Science Foundation for Research and Technology, Greece-Eigen face methodFace Recog nition Using Eigenfaces, Matthew A. Turk and Alex P. Pentland, Vi