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The sampling method returns a distribution over possible head poses.
As the result, the computation speed of this combination fulfills the requirements and the method returns a great number of detected feature points while losing very little precision.
Then, in the most general case, a policy search method returns a probability distribution P over Π representing the uncertainty over the optimal policy parameters.
The parametric weighting can be applied only if the ranking method returns a numeric value as output, not just a position.
In fact, if the Newton-Raphson method returns a non-feasible (P_{g}^{textmd {tiny (II)}}), the set Π g and the associated (hat {N}_{g}), Q g, and X g are required to be updated.
The descriptor of head pose is comprised of skin and nonskin pixels, which enables us to estimate 8 distinct head poses, as shown in Figure 2. A fast sampling method returns a distribution over previously seen head poses, which we now describe in detail.
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The HCP method returns an average total execution time equal to 69 milliseconds whereas our method returns only 58 milliseconds for the same DFG.
Estimating the noise model by the Park method returns an α ^ = 0.005.
Bills et al's method returns an error of 346.614 mm, even with the combination of 25 scan contours and a point pitch of 0.5 mm to give a total number of 2000 points.
If the sequence of services in a route is feasible with respect to vehicle capacity and maximum ride times of the patients, the method returns an efficient scheduling for this route.
This provides an effective language support for active libraries: namely, a (library) class can provide a method returning a customized version of a class, depending, e.g., on the execution platform.
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