To realize natural interaction in a semi-virtual reality (SVR) system, hand pose estimation is a crucial step of human-computer interaction (HCI) in a semi-virtual reality cockpit. In order to enhance the sense of immersion for the pilot in the semi-virtual reality cockpit, a hand pose estimation method based on maximum a posteriori (MAP) framework is proposed in this paper. Under the MAP framework, a multi-view tree that contains information of multiple cameras is put forward to deal with the self-occlusion in hand motion. Hand gesture parameters are estimated by searching among the tree nodes. In this method, temporal consistency is used to advance the estimated accuracy, and locality sensitive hashing (LSH) is improved to raise the efficiency in the tree searching algorithm. Experimental results show that the proposed algorithm possesses the characteristic of real-time and accurate rendering of the virtual hand and the ability to reconstruct hand postures in a semi-virtual reality cockpit.
ZHOU Lai, GU Hongbin, SUN Jin, TANG Yong
. Hand Pose Estimation Based on Maximum a Posteriori Framework in Semi-virtual Reality Cockpit[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011
, 32(7)
: 1252
-1259
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DOI: CNKI:11-1929/V.20101228.1335.005
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