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Real-time 3D Feature Extraction Combined with 3D Reconstruction  

Hong, Kwang-Jin (숭실대학교 미디어학과)
Lee, Chul-Han (숭실대학교 미디어학과)
Jung, Kee-Chul (숭실대학교 미디어학과)
Oh, Kyoung-Su (숭실대학교 미디어학과)
Publication Information
Journal of KIISE:Software and Applications / v.35, no.12, 2008 , pp. 789-799 More about this Journal
Abstract
For the communication between human and computer in an interactive computing environment, the gesture recognition has been studied vigorously. The algorithms which use the 2D features for the feature extraction and the feature comparison are faster, but there are some environmental limitations for the accurate recognition. The algorithms which use the 2.5D features provide higher accuracy than 2D features, but these are influenced by rotation of objects. And the algorithms which use the 3D features are slow for the recognition, because these algorithms need the 3d object reconstruction as the preprocessing for the feature extraction. In this paper, we propose a method to extract the 3D features combined with the 3D object reconstruction in real-time. This method generates three kinds of 3D projection maps using the modified GPU-based visual hull generation algorithm. This process only executes data generation parts only for the gesture recognition and calculates the Hu-moment which is corresponding to each projection map. In the section of experimental results, we compare the computational time of the proposed method with the previous methods. And the result shows that the proposed method can apply to real time gesture recognition environment.
Keywords
Real-time 3D Feature Extraction; Gesture Recognition; Computer Vision; Projection Map; Visual Hull;
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