Hand gesture recognition system received great attention in the recent few years because of its manifoldness applications and the ability to interact with machine efficiently through human computer interaction. In this paper a survey of recent hand gesture recognition systems is presented. Key issues of hand gesture recognition system are presented with challenges of gesture system. Review methods of recent postures and gestures recognition system presented as well. Summary of research results of hand gesture methods, databases, and comparison between main gesture recognition phases are also given. Advantages and drawbacks of the discussed systems are explained finally.
Keywords
Hand Posture, Hand Gesture, Human Computer Interaction (HCI), Segmentation, Feature Extraction, Classification Tools, Neural Networks.
Conclusion
In this paper various methods are discussed for gesture recognition, these methods include from Neural Network, HMM, fuzzy c-means clustering, besides using orientation histogram for features representation. For dynamic gestures HMM tools are perfect and have shown its efficiency especially for robot control [20][16]. NNs are used as classifier [8][25] and for capturing hand shape in [14]. For features extraction, some methods and algorithms are required even to capture the shape of the hand as in [15][17][18], [17] applied Gaussian bivariate function for fitting the segmented hand which used to minimize the rotation affection [17][18]. The selection of specific algorithm for recognition depends on the application needed. In this work application areas for the gestures system are presented. Explanation of gesture recognition issues, detail discussion of recent recognition systems are given as well. Summary of some selected systems are listed as well.
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How to Cite This Paper
Koppula Venkat Sai, Kudumula Prabhanjan Reddy, Karru Sai Vardhan Reddy, Mr.C.Rama chandran (2026). Hand Gesture Recognition: A Literature Review. International Journal of Computer Techniques, 13(2). ISSN: 2394-2231.
