The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Comparative Study of Machine Learning Techniques for Gesture Recognition Using Kinect
|
|
Author(s): Rodrigo Ibañez (ISISTAN (UNICEN-CONICET) Research Institute, Argentina), Alvaro Soria (ISISTAN (UNICEN-CONICET) Research Institute, Argentina), Alfredo Raul Teyseyre (ISISTAN (UNICEN-CONICET) Research Institute, Argentina), Luis Berdun (ISISTAN (UNICEN-CONICET) Research Institute, Argentina)and Marcelo Ricardo Campo (ISISTAN (UNICEN-CONICET) Research Institute, Argentina)
Copyright: 2020
Pages: 22
Source title:
Cognitive Analytics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-2460-2.ch056
Purchase
|
Abstract
Progress and technological innovation achieved in recent years, particularly in the area of entertainment and games, have promoted the creation of more natural and intuitive human-computer interfaces. For example, natural interaction devices such as Microsoft Kinect allow users to explore a more expressive way of human-computer communication by recognizing body gestures. In this context, several Supervised Machine Learning techniques have been proposed to recognize gestures. However, scarce research works have focused on a comparative study of the behavior of these techniques. Therefore, this chapter presents an evaluation of 4 Machine Learning techniques by using the Microsoft Research Cambridge (MSRC-12) Kinect gesture dataset, which involves 30 people performing 12 different gestures. Accuracy was evaluated with different techniques obtaining correct-recognition rates close to 100% in some results. Briefly, the experiments performed in this chapter are likely to provide new insights into the application of Machine Learning technique to facilitate the task of gesture recognition.
Related Content
|
Jaime Salvador, Zoila Ruiz, Jose Garcia-Rodriguez.
© 2020.
12 pages.
|
|
Stavros Pitoglou.
© 2020.
11 pages.
|
|
Mette L. Baran.
© 2020.
13 pages.
|
|
Yingxu Wang, Victor Raskin, Julia M. Rayz, George Baciu, Aladdin Ayesh, Fumio Mizoguchi, Shusaku Tsumoto, Dilip Patel, Newton Howard.
© 2020.
15 pages.
|
|
Yingxu Wang, Lotfi A. Zadeh, Bernard Widrow, Newton Howard, Françoise Beaufays, George Baciu, D. Frank Hsu, Guiming Luo, Fumio Mizoguchi, Shushma Patel, Victor Raskin, Shusaku Tsumoto, Wei Wei, Du Zhang.
© 2020.
18 pages.
|
|
Nayem Rahman.
© 2020.
24 pages.
|
|
Amir Manzoor.
© 2020.
27 pages.
|
|
|