Hand Pose Estimation Using Expectation-Constrained-Maximization From Voxel Data
نویسندگان
چکیده
This paper describes voxel-based hand posture estimation using the Expectation Constrained-Maximization framework to estimate the parameters to a 16 segment 24 degreesof-freedom hand model. This method uses only voxels to estimate finger segment locations and orientations. The hand model consists of a mixture of kinematically constrained 3D gaussian distributions. Results on simulated and real data show that given a good initial conditions, this proposed iterative model parameter estimation process converges to the ”voxelized” hand.
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تاریخ انتشار 2004