%0 Conference Paper %1 lahiani2018estimation %A Lahiani, Houssem %A Kherallah, Monji %A Neji, Mahmoud %B Intelligent Systems Design and Applications %C Cham %D 2018 %E Abraham, Ajith %E Muhuri, Pranab Kr. %E Muda, Azah Kamilah %E Gandhi, Niketa %I Springer %K adaboost android feature gesture haar haar-like hand hci human-computer-interaction mobile real recognition %P 619-629 %R 10.1007/978-3-319-76348-4_60 %T Hand Pose Estimation System Based on a Cascade Approach for Mobile Devices %U https://doi.org/10.1007/978-3-319-76348-4_60 %X The rise in the use of mobile devices requires finding new ways to interact with this type of devices. Gestures are an effective way to interact with the mobile device and to place order to it. However, gesture recognition in this context constitute a challenging task due the limited computational capacities of this type of devices. In this work, we present a hand pose estimation system for mobile device. The gesture is recognized by using a boosting algorithm and Haar-like features. The system is designed for Android devices. The method used consists of capturing gestures by a smartphone's camera to recognize the hand sign. It presents a system based on a real-time hand posture recognition algorithm for mobile devices. The aim of this system is to allow the mobile device interpreting hand signs made by users without the need to touch the screen. %@ 978-3-319-76348-4

@inproceedings{lahiani2018estimation, abstract = {The rise in the use of mobile devices requires finding new ways to interact with this type of devices. Gestures are an effective way to interact with the mobile device and to place order to it. However, gesture recognition in this context constitute a challenging task due the limited computational capacities of this type of devices. In this work, we present a hand pose estimation system for mobile device. The gesture is recognized by using a boosting algorithm and Haar-like features. The system is designed for Android devices. The method used consists of capturing gestures by a smartphone's camera to recognize the hand sign. It presents a system based on a real-time hand posture recognition algorithm for mobile devices. The aim of this system is to allow the mobile device interpreting hand signs made by users without the need to touch the screen.}, added-at = {2019-11-15T23:22:31.000+0100}, address = {Cham}, author = {Lahiani, Houssem and Kherallah, Monji and Neji, Mahmoud}, biburl = {https://www.bibsonomy.org/bibtex/2c0ec4cbca0d5b2824d51d7ede699984a/jpmor}, booktitle = {Intelligent Systems Design and Applications}, description = {Hand Pose Estimation System Based on a Cascade Approach for Mobile Devices | SpringerLink}, doi = {10.1007/978-3-319-76348-4_60}, editor = {Abraham, Ajith and Muhuri, Pranab Kr. and Muda, Azah Kamilah and Gandhi, Niketa}, eventdate = {2017}, eventtitle = {Intelligent Systems Design and Applications (ISDA)}, interhash = {f6ad444be94c83a6d2302b427c2f35a3}, intrahash = {c0ec4cbca0d5b2824d51d7ede699984a}, isbn = {978-3-319-76348-4}, keywords = {adaboost android feature gesture haar haar-like hand hci human-computer-interaction mobile real recognition}, language = {English}, pages = {619-629}, publisher = {Springer}, school = {University of Sfax}, timestamp = {2020-10-07T13:36:50.000+0200}, title = {Hand Pose Estimation System Based on a Cascade Approach for Mobile Devices}, url = {https://doi.org/10.1007/978-3-319-76348-4_60}, year = 2018 }