ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Research of Visual Interaction for Virtual Reality Flight Training
Received date: 2013-01-11
Revised date: 2013-05-22
Online published: 2013-06-17
Supported by
National Natural Science Foundation of China (51305255,61039002);Natural Science Foundation of Shanghai City (13ZR1455900)
Appearance-based hand pose estimation which relies on computer vision techniques is adopted to realize natural interaction in a semi-virtual reality cockpit. To cope with the low efficiency and high memory consumption in large capacity and high-dimension feature indexing, an improved locality sensitive Hashing (LSH) method is proposed in this paper which combines the multi-probe principle with the nearest-neighbor table. Moreover, a forecast model which predicts indexing performance and a parameter optimization method are used to achieve better indexing performance. Experimental results show that the forecast model is appropriate for practical indexing performances and the time consumption is reduced by 41.9% at the cost of a slight recall rate drop. In summary, the application of the improved LSH to hand pose estimations able to upgrade virtual hand visualization and hand posture reconstruction in a semi-virtual reality cockpit.
ZHOU Lai , ZHENG Danli , GU Hongbin , WANG Debao . Research of Visual Interaction for Virtual Reality Flight Training[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013 , 34(10) : 2391 -2401 . DOI: 10.7527/S1000-6893.2013.0290
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