Abstract
The computer vision approach is most widely used for research related to hand gesture recognition. The detection of the image orientation has been discovered to be one of the keys to determine its success. The degree of freedom for a hand determines the shape and orientation of a gesture, which further causes a problem in the recognition methods. This article proposed evaluating orientation detection for silhouette static hand gestures with different poses and orientations without considering the forearm. The longest chord and ellipse were the two popular methods compared. The angles formed from two wrist points were selected as ground truth data and calculated from the horizontal axis. The performance was analyzed using the error values obtained from the difference in ground truth data angles compared to the method's results. The method has errors closer to zero that were rated better. Moreover, the method was evaluated using 1187 images, divided into four groups based on the forearm presence, and the results showed its effect on orientation detection. It was also discovered that the ellipse method was better than the longest chord. This study's results are used to select hand gesture orientation detection to increase accuracy in the hand gesture recognition process.
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