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Learning to Associate: HybridBoosted Multi-Target Tracker for Crowded Scene

Learning to Associate: HybridBoosted Multi-Target Tracker for Crowded Scene. Present by 陳群元. review. review. Strong ranking classifier. Strong ranking classifier. weak. weak. weak. weak. Update sample weight. Update weight. Update weight. Weak ranking classifier.

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Learning to Associate: HybridBoosted Multi-Target Tracker for Crowded Scene

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  1. Learning to Associate: HybridBoosted Multi-Target Tracker for Crowded Scene Present by 陳群元

  2. review

  3. review

  4. Strong ranking classifier Strong ranking classifier weak weak weak weak Update sample weight Update weight Update weight

  5. Weak ranking classifier

  6. previous problem • The lengths of ground truth tracklets are equal. tracklet tracklet tracklet tracklet Low Z value tracklet

  7. solution • Cut trajectory to tracklet randomly tracklet tracklet tracklet tracklet

  8. Previous problem • The scales of some thresholds are wide. Feature 1 Feature 5

  9. solution • Quantize these features’ threshold with respective bins. • Quantize the difference of min and max value with difference bin.

  10. System Architecture

  11. To do • Human detection • Build ground truth • association

  12. demo

  13. The end • Thank you!

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