Object detection method based on feature redundancy elimination AdaBoost classifier
An object detection and classifier technology, which is applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve the problems of large computing time, reduced learning speed, large difference, etc., and achieves a simple, high-efficiency, high-real-time method. Effects of Sex and Processing Speed
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[0030] The following is a further description of the method proposed in this paper in combination with the haar feature detection process of the object:
[0031] The present invention uses the object detection method of weight-based redundant feature reduction AdaBoost classifier, such as figure 1 As shown, it specifically includes the following steps:
[0032] Step 1, classifier training, such as figure 2 shown.
[0033] (1) Input: a feature set F={f 1 ,..., f K} and S={(x 1 ,y 1 ),..., (x N ,y N )} This is a labeled training set where y i ={0, 1} respectively correspond to positive samples and negative samples, a combined classifier h and a given cycle number T, elimination coefficient λ, and association threshold γ.
[0034] (2) Initialization: Dataset Initialize training sample weights: when y i = 0, when y j = 1, Among them, m and l represent the number of negative samples and positive samples respectively, and the feature weight D: d 1,i = 1.0, feature...
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