Immersive rehabilitation monitoring system supported with Augmented Reality

Main Article Content

Adam Wojciechowski
Artur Majewski
Piotr Napieralski
Przemysław Nowak
Tadeusz Poreda


Keywords : augmented reality, passive rehabilitation, depth controller
Abstract
Gender recognition, across different races and regardless of age, is becoming an increasingly important technology in the domains of marketing, human-computer interaction and security. Most state-of-the-art systems consider either highly constrained conditions or relatively large databases. In either case, often not enough attention is paid to cross-racial age-invariant applications. This paper proposes a~method of hybrid classification, which performs well even with a small training set. The design of the classifier enables the construction of reliable decision boundaries insensitive to an aging model as well as to race variation. For a training set consisting of one hundred images, the proposed method reached an accuracy level of 90%, whereas the best method known from the literature, tested under the restrictions imposed on the database, achieved only 78% accuracy.

Article Details

How to Cite
Wojciechowski, A., Majewski, A., Napieralski, P., Nowak, P., & Poreda, T. (2015). Immersive rehabilitation monitoring system supported with Augmented Reality. Machine Graphics and Vision, 24(1/4), 3–15. https://doi.org/10.22630/MGV.2015.24.1.1
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