Adapting Viola-Jones Method for Online Hand / Glove Identification
This article proposes a method for hand identification, adapting the method of Viola-Jones for identifying two different objects. The main objective of this work is to solve the problems of hand identification. Thus, our approach based on learning for two objects as one package. Also, the proposed method folds into three parts; the first part is training for both objects, second detection of both objects, and third the identification step to identify if the hand is wearing a glove or not, then labeling each one with a suitable state. Moreover, to test our method, we have proposed a new dataset, which includes a variety of cases with different compositions of hand. As a result, 8 cases were used to test the method. The method was able to detect a human hand successfully. Additionally, it could identify whether the hand was or was not wearhing a glove. The accuracy of detecting a hand without a glove was about 63%, and the accuracy of detecting a hand with a glove on was about 61%. Even though the tests scored different accuracy, as a first step towards solving this problem, it is a big achievement to even reach this level of accuracy.
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