@article {593, title = {Automatic recognition of the American sign language fingerspelling alphabet to assist people living with speech or hearing impairments}, journal = {Journal of Ambient Intelligence and Humanized Computing}, year = {2017}, pages = {1{\textendash}11}, abstract = {

Sign languages are natural languages used mostly by deaf and hard of hearing people. Different development opportunities for people with these disabilities are limited because of communication problems. The advances in technology to recognize signs and gestures will make computer supported interpretation of sign languages possible. There are more than 137 different sign languages around the world; therefore, a system that interprets them could be beneficial to all, especially to the Deaf Community. This paper presents a system based on hand tracking devices (Leap Motion and Intel RealSense), used for signs recognition. The system uses a Support Vector Machine for sign classification. Different evaluations of the system were performed with over 50 individuals; and remarkable recognition accuracy was achieved with selected signs (100{\%} accuracy was achieved recognizing some signs). Furthermore, an exploration on the Leap Motion and the Intel RealSense potential as a hand tracking devices for sign language recognition using the American Sign Language fingerspelling alphabet was performed.

}, keywords = {American sign language, Automatic sign language recognition, Intel realsense, Leap Motion, Natural user interfaces, Support vector machine}, issn = {1868-5145}, doi = {10.1007/s12652-017-0475-7}, url = {http://dx.doi.org/10.1007/s12652-017-0475-7}, author = {Quesada, Luis and L{\'o}pez, Gustavo and Guerrero, Luis} } @inbook {473, title = {Improving Deaf People Accessibility and Communication Through Automatic Sign Language Recognition Using Novel Technologies}, booktitle = {Advances in Design for Inclusion}, volume = {500}, year = {2016}, pages = {497{\textendash}507}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {

Communication is a key for human development. Nevertheless, deaf people have difficulty interacting with hearing and hard of hearing people. On the other hand, new technology allows gesture recognition. This work aims to promote the development of tools to take advantage of 3D camera technology for the benefit of the Deaf Community around the world. This research proposes a sign recognition model using 3d cameras (i.e. Leap Motion and Intel RealSense) and support vector machines (SVM). The goal is to support the communication process between deaf and hearing people. Furthermore, we conduct an experiment determining an appropriate amount of training sample signs to ensure satisfactory results using SVMs.

}, keywords = {American sign language, Intel realsense, Leap Motion, Sign language recognition}, isbn = {978-3-319-41962-6}, doi = {10.1007/978-3-319-41962-6_44}, url = {http://dx.doi.org/10.1007/978-3-319-41962-6_44}, author = {Quesada, Luis and L{\'o}pez, Gustavo and Guerrero, Luis}, editor = {Di Bucchianico, Giuseppe and Kercher, Pete} } @inbook {530, title = {A Gesture-Based Interaction Approach for Manipulating Augmented Objects Using Leap Motion}, booktitle = {Ambient Assisted Living. ICT-based Solutions in Real Life Situations}, volume = {9455}, year = {2015}, pages = {231-243}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, abstract = {

Ambient Intelligence and Ubiquitous Computing are carrying the world to a reality where almost every object interacts with the environment, either via sensors or actuators, and users must learn how to interact with such systems. This paper presents a gesture-based interaction approach to manipulate such objects. We developed a prototype using a leap motion controller as a hand-tracking device, and a Support Vector Machine as a classifier to distinguish between gestures. Our system was evaluated by 12 users with over 10 commands. We also show a review on gesture-based interaction and compare other proposals with ours.

}, keywords = {Gesture-Based interaction, Leap Motion, Ubiquitous systems}, isbn = {978-3-319-26409-7}, doi = {10.1007/978-3-319-26410-3_22}, url = {http://dx.doi.org/10.1007/978-3-319-26410-3_22}, author = {L{\'o}pez, Gustavo and Quesada, Luis and Guerrero, LuisA.}, editor = {Cleland, Ian and Guerrero, Luis and Bravo, Jos{\'e}} } @conference {798, title = {Sign Language Recognition Using Leap Motion}, booktitle = {Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information}, year = {2015}, month = {12/2015}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {

Several million people around the world use signs as their main mean of communication. The advances in technologies to recognize such signs will make possible the computer supported interpretation of sign languages. There are more than 137 different sign language around the world; therefore, a system that interprets those languages could be beneficial to all, including the Deaf Community. This paper presents a system based on a hand tracking device called Leap Motion, used for signs recognition. The system uses a Support Vector Machine for sign classification. We performed three different evaluations of our system with over 24 people.

}, keywords = {American sign language, Automatic sign language recognition, Leap Motion, Support vector machine}, isbn = {978-3-319-26401-1}, doi = {https://doi.org/10.1007/978-3-319-26401-1_26}, url = {https://link.springer.com/chapter/10.1007/978-3-319-26401-1_26}, author = {Quesada, Luis and L{\'o}pez, Gustavo and Guerrero, Luis A.}, editor = {Garc{\'\i}a-Chamizo, Juan M. and Fortino, Giancarlo and Ochoa, Sergio F.} }