Abstract
Development of human-computer interaction methods tends to exploit more and more natural human activities like thoughts, body posture or hands gesticulation. While most of authors improve whole body tracking this paper concentrates on hand's poses analysis. Due to the usage of the depth image based object recognition approach to hand pose estimation a very precise method was obtained. Additionally thanks to decision forest implemented on GPU a real-time processing is possible. © 2012 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Półrola, M., & Wojciechowski, A. (2012). Real-time hand pose estimation using classifiers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7594 LNCS, pp. 573–580). Springer Verlag. https://doi.org/10.1007/978-3-642-33564-8_69
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