The Scientific World Journal / 2013 / Article / Alg 1

Research Article

Reinforced AdaBoost Learning for Object Detection with Local Pattern Representations

Algorithm 1

Proposed update procedure of a classifier based on a reinforced Adaboost learning.
: Number of positive samples, : Number of negative samples
: LPR of ith positive sample, : LPR of ith negative sample
: labels (+1: positive, −1: negative)
(1) Initialize sample weights
(2) For do
 (a) Generate histograms of LPR from positive samples and negative samples
: indicator function that takes 1 if the argument is true and 0 otherwise
  (b) Compute error rate
  (c) Select the best pixel location with the smallest error rate
: the maximum number of pixel locations allowed
: the set of pixel locations already chosen before,
  (d) Create a lookup table for the weak classifier of pixel location
  (e) Update the sample weights & Normalization
(3) Obtain pixel classifier of a single pixel location x
Constructed strong classifier

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