REAL TIME FACE DETECTION
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Transcript of REAL TIME FACE DETECTION
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REAL TIME FACE DETECTION
Justin RillingPooja MhapsekarMoinuddin Sayed
Ogom J Obinor
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IntroductionIntroduction
• The idea is to be able to detect faces appearing in an image.
• The faces can be of different sizes and orientations.
• The motivation behind implementing this on an FPGA is that image processing is inherently parallel in nature and lends itself well to an FPGA.
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Viola and Jones’ DetectorViola and Jones’ Detector
Key Contributions
1. Integral Image – fast computation of features used by the detector.
2. Combines complex classifiers in “cascade” – focus on facial features.
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Integral ImageIntegral Image
• Major contribution of the Viola and Jones detector.
• Summation of pixel values of the original image.
• Value at location (x,y) = sum of values of pixels above and to the left of (x,y).
• Whole image converted to integral image and a window buffer used to scan the entire image.
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Haar ClassifiersHaar Classifiers
• Classifiers are composed of 2-3 rectangles.
• Weights and sizes associated with features – obtained through AdaBoost.
• Classifier sum = ∑ (area * weights)
• Integral image makes area calculation easy. Area = L4–L3–L2+L1.
• Several classifiers compose a stage.
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StageStage
• Sum of all Haar feature classifiers compared with the stage threshold.
• Multiple stages, each stage has different number of classifiers.
• Threshold obtained from AdaBoost algorithm.
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Face Detection Example
0.0Classifier Sum
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Face Detection Example
426Classifier Sum
< 542Classifier Threshold
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Face Detection Example
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Face Detection Example
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Face Detection Example
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0.1514132Left Value0.1852073
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Face Detection Example
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Face Detection Example
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0.0900493Left Value0.2752566
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Face Detection Example
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0.0900493Left Value0.2752566
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Window Buffer Failed Stage 0
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Face Detection Example
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Face Detection Example
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Face Detection Example
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Face Detection Example
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Face Detection Example
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Face Detection Example
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Face Detection Example
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Top Level DesignTop Level Design
YES
Get ScaledImage
Get Integral Image
Window Buffer (21x21)
Face Detection PipelineEnd of
Image?
NO
Monitor
Draw RectangleIf face is det.
Get Image
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Face Detection Pipeline
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Original End Product
USB Webcam FPGA Display
USB DVI
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Updated End Product
Digital Interface
1/3 Color Camera Mod C3188A-6018• Supports several standard image data
formats including YCrCb 4:2:2 • 640 x 480 resolution• 5 V signaling • 30 fps
FPGA Display DVI
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3.3 VSignaling
Updated End Product
XC95144XLCPLD
Display
5 VSignaling
DVI1/3 Color Camera Mod C3188A-6018• Supports several standard image data
formats including YCrCb 4:2:2 • 640 x 480 resolution• 5 V signaling • 30 fps
FPGA
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DVI Controller
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Questions ???
References:
1. P. Viola and M. Jones, “Robust real-time object detection,” International Journal of Computer Vision, 57(2), 137-154, 2004.
2. Junguk Cho, Shahnam Mirzaei, Jason Oberg, Ryan Kastner, “FPGA-Based Face Detection System Using Haar Classifiers,” Proceeding of the ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 103-112, 2009.
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OpenCV Program – Lena.jpg
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OpenCV Program – ER.jpg
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OpenCV Program – ER.jpgWindow Buffer (2, 152, 122)Window Buffer (2, 152, 122)
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Face Detection Pipeline
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OpenCV Program – ER.jpgWindow Buffer (3, 165, 20)Window Buffer (3, 165, 20)
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Face Detection Pipeline
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Questions ???