%0 Journal Article %1 alshamayleh2018systematic %A Al-Shamayleh, Ahmad Sami %A Ahmad, Rodina %A Abushariah, Mohammad A. M. %A Alam, Khubaib Amjad %A Jomhari, Nazean %D 2018 %I Springer %J Multimedia Tools and Applications %K computer-vision gesture-recognition human-computer-interaction real systematic-literature-review vision-based-gesture-recognition %N 21 %P 28121-28184 %R 10.1007/s11042-018-5971-z %T A Systematic Literature Review on Vision Based Gesture Recognition Techniques %U https://doi.org/10.1007/s11042-018-5971-z %V 77 %X Human Computer Interaction (HCI) technologies are rapidly evolving the way we interact with computing devices and adapting to the constantly increasing demands of modern paradigms. One of the most useful tools in this regard is the integration of Human-to-Human Interaction gestures to facilitate communication and expressing ideas. Gesture recognition requires the integration of postures, gestures, face expressions and movements for communicating or conveying certain messages. The aim of this study is to aggregate and synthesize experiences and accumulated knowledge about Vision-Based Recognition (VBR) techniques. The major objective of conducting this Systematic Literature Review (SLR) is to highlight the state-of-the-art in the context of vision-based gesture recognition with specific focus on hand gesture recognition (HGR) techniques and enabling technologies. After a careful systematic selection process, 100 studies relevant to the four research questions were selected. This process was followed by data collection, a detailed analysis, and a synthesis of the selected studies. The results reveal that among the VBR techniques, HGR is a predominant and highly focused area of research. Research focus is also found to be converging towards sign language recognition. Potential applications of HGR techniques include desktop applications, smart environments, entertainment, sign language interpretation, virtual reality and gamification. Although various experimental research efforts have been devoted to gestures recognition, there are still numerous open issues and research challenges in this field. Lastly, considering the results from this SLR, potential future research directions are suggested, including a much needed focus on grammatical interpretation, hybrid approaches, smartphone devices, normalization, and real-life systems.

@article{alshamayleh2018systematic, abstract = {Human Computer Interaction (HCI) technologies are rapidly evolving the way we interact with computing devices and adapting to the constantly increasing demands of modern paradigms. One of the most useful tools in this regard is the integration of Human-to-Human Interaction gestures to facilitate communication and expressing ideas. Gesture recognition requires the integration of postures, gestures, face expressions and movements for communicating or conveying certain messages. The aim of this study is to aggregate and synthesize experiences and accumulated knowledge about Vision-Based Recognition (VBR) techniques. The major objective of conducting this Systematic Literature Review (SLR) is to highlight the state-of-the-art in the context of vision-based gesture recognition with specific focus on hand gesture recognition (HGR) techniques and enabling technologies. After a careful systematic selection process, 100 studies relevant to the four research questions were selected. This process was followed by data collection, a detailed analysis, and a synthesis of the selected studies. The results reveal that among the VBR techniques, HGR is a predominant and highly focused area of research. Research focus is also found to be converging towards sign language recognition. Potential applications of HGR techniques include desktop applications, smart environments, entertainment, sign language interpretation, virtual reality and gamification. Although various experimental research efforts have been devoted to gestures recognition, there are still numerous open issues and research challenges in this field. Lastly, considering the results from this SLR, potential future research directions are suggested, including a much needed focus on grammatical interpretation, hybrid approaches, smartphone devices, normalization, and real-life systems.}, added-at = {2019-11-14T08:15:24.000+0100}, author = {Al-Shamayleh, Ahmad Sami and Ahmad, Rodina and Abushariah, Mohammad A. M. and Alam, Khubaib Amjad and Jomhari, Nazean}, biburl = {https://www.bibsonomy.org/bibtex/2ab37dd61b5c6068039e5fb8380726eea/jpmor}, day = 01, description = {A systematic literature review on vision based gesture recognition techniques | SpringerLink}, doi = {10.1007/s11042-018-5971-z}, interhash = {aab3118a2a7eac0e58a00c9de4325ee8}, intrahash = {ab37dd61b5c6068039e5fb8380726eea}, issn = {1573-7721}, journal = {Multimedia Tools and Applications}, keywords = {computer-vision gesture-recognition human-computer-interaction real systematic-literature-review vision-based-gesture-recognition}, language = {English}, month = {11}, number = 21, pages = {28121-28184}, publisher = {Springer}, school = {University of Malaya (UM)}, timestamp = {2020-10-07T13:36:50.000+0200}, title = {A Systematic Literature Review on Vision Based Gesture Recognition Techniques}, url = {https://doi.org/10.1007/s11042-018-5971-z}, volume = 77, year = 2018 }