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Pete Barnum March 8, 2006

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

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Pete Barnum March 8, 2006

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  1. Pete Barnum March 8, 2006 Pedestrian DetectionHistograms of Oriented Gradients for Human DetectionNavneet Dalal and Bill Triggs CVPR ‘05

  2. Challenges • Wide variety of articulated poses • Variable appearance/clothing • Complex backgrounds • Unconstrained illumination • Occlusions • Different Scales

  3. Slides from Sminchisescu

  4. Slides from Sminchisescu

  5. Slides from Sminchisescu

  6. 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)

  7. Tested with • RGB • LAB • Grayscale • Gamma Normalization and Compression • Square root • Log

  8. centered diagonal uncentered cubic-corrected Sobel

  9. Histogram of gradient orientations -Orientation -Position • Weighted by magnitude

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