Hand gesture recognition algorithm combining hand-type adaptive algorithm and effective-area ratio for efficient edge computing

Abstract

Most existing gesture recognition algorithms have low recognition rates under rotation, translation, and scaling of hand images as well as different hand types. We propose a new hand gesture recognition algorithm that combines the hand-type adaptive algorithm and effective-area ratio based on feature matching. Samples are divided into several groups according to the subjects' palm shapes and the algorithm is trained using self-collected data. The user's hand type is paired with one of the sample libraries by the hand-type adaptive algorithm. To further improve the accuracy, the effective-area ratio of the gesture is calculated based on the minimum bounding rectangle, and the preliminary gesture is recognized by the effective-area ratio feature method. The results of experiments demonstrate that the proposed algorithm could accurately recognize gestures in real time and exhibits good adaptability to different hand types. The overall recognition rate is over 94%. The recognition rate still exceeds 93% when hand gesture images are rotated, translated, or scaled.

A Deep Learning Framework for Hand Gesture Recognition and Multimodal Interface Control

“…Zhang et al [15] provided an innovative approach to gesture recognition that combines a hand shape adaptive algorithm with an effective area ratio calculation. The authors collected data and categorized the samples into different groups based on the shape of the subjects' palms, using this information to train their algorithm.…”

Static hand gesture recognition based on hierarchical decision and classification of finger features

“…These features were fed into the long-short time memory recurrent neural network to predict the gesture. Zhang et al 35 proposed a hand gesture recognition algorithm based on geometric features. Some length parameters of the palms were used to divide the hand gestures into different types firstly, and the area-perimeter ratio and effective-area ratio of the hand gesture were extracted for gesture recognition.…”