Pedestrian Detection Histograms of Oriented Gradients for Human Detection Navneet Dalal and Bill Triggs CVPR ‘05 - PowerPoint PPT Presentation

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Pedestrian Detection Histograms of Oriented Gradients for Human Detection Navneet Dalal and Bill Triggs CVPR ‘05. Pete Barnum March 8, 2006. Challenges. Wide variety of articulated poses Variable appearance/clothing Complex backgrounds Unconstrined illumination Occlusions

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Pedestrian Detection Histograms of Oriented Gradients for Human Detection Navneet Dalal and Bill Triggs CVPR ‘05

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Pedestrian DetectionHistograms of Oriented Gradients for Human DetectionNavneet Dalal and Bill Triggs CVPR ‘05

Pete Barnum

March 8, 2006


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Challenges

  • Wide variety of articulated poses

  • Variable appearance/clothing

  • Complex backgrounds

  • Unconstrined illumination

  • Occlusions

  • Different Scales


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Slides from Sminchisescu


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Slides from Sminchisescu


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Slides from Sminchisescu


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Feature Sets

  • Haar wavelets + SVM:

    • Papageorgiou & Poggio (2000)

    • Mohan et al (2001)

    • DePoortere et al (2002)

  • Rectangular differential features + adaBoost:

    • Viola & Jones(2001)

  • Parts based binary orientation position histogram + adaBoost:

    • Mikolajczk et al (2004)

  • Edge templates + nearest neighbor:

    • Gavrila & Philomen (1999)

  • Dynamic programming:

    • Felzenszwalb & Huttenlocher (2000),

    • Loffe & Forsyth (1999)

  • Orientation histograms:

    • C.F. Freeman et al (1996)

    • Lowe(1999)

  • Shape contexts:

    • Belongie et al (2002)

  • PCA-SIFT:

    • Ke and Sukthankar (2004)


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  • Tested with

    • RGB

    • LAB

    • Grayscale

  • Gamma Normalization and Compression

    • Square root

    • Log


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centered

diagonal

uncentered

cubic-corrected

Sobel


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  • Histogram of gradient orientations

    -Orientation -Position

    • Weighted by magnitude


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