@inproceedings{2dbe8bc57b04402e987a31e3f317a114,
title = "Shape Trajectory Analysis Based on HOG Descriptor for Isolated Word Sign Language Recognition",
abstract = "Sign language is based principally on hands gestures. To have a robust recognition system, each hand modality must be correctly presented using both motion and shape descriptors. This paper proposes an enhanced isolated word sign language recognition system based on hands trajectories analysis able to solve the most challenges such as signer{\textquoteright}s interchangeability and speed variation. In this context, Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) are introduced. The performance of our proposed system is tested on public databases (RWTH-Boston-50 and RWTH-Boston-104) with signer-independent condition and outperformed the recent existing works.",
author = "Sana Fakhfakh and \{Ben Jemaa\}, Yousra",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 36th International Conference on Advanced Information Networking and Applications, AINA 2022 ; Conference date: 13-04-2022 Through 15-04-2022",
year = "2022",
doi = "10.1007/978-3-030-99619-2\_5",
language = "English",
isbn = "9783030996185",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "46--54",
editor = "Leonard Barolli and Farookh Hussain and Tomoya Enokido",
booktitle = "Advanced Information Networking and Applications - Proceedings of the 36th International Conference on Advanced Information Networking and Applications AINA-2022",
address = "Germany",
}