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Decoupling C++ code so that AU detection works properly with a new PDM.
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@@ -769,14 +769,16 @@ bool CLNF::Fit(const cv::Mat_<uchar>& im, const cv::Mat_<float>& depthImg, const
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if(parameters.refine_parameters == true)
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{
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// Adapt the parameters based on scale (wan't to reduce regularisation as scale increases, but increa sigma and tikhonov)
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tmp_parameters.reg_factor = parameters.reg_factor - 15 * log(patch_experts.patch_scaling[scale]/0.25)/log(2);
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int scale_max = scale >= 2 ? 2 : scale;
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// Adapt the parameters based on scale (wan't to reduce regularisation as scale increases, but increase sigma and Tikhonov)
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tmp_parameters.reg_factor = parameters.reg_factor - 15 * log(patch_experts.patch_scaling[scale_max]/0.25)/log(2);
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if(tmp_parameters.reg_factor <= 0)
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tmp_parameters.reg_factor = 0.001;
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tmp_parameters.sigma = parameters.sigma + 0.25 * log(patch_experts.patch_scaling[scale]/0.25)/log(2);
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tmp_parameters.weight_factor = parameters.weight_factor + 2 * parameters.weight_factor * log(patch_experts.patch_scaling[scale]/0.25)/log(2);
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tmp_parameters.sigma = parameters.sigma + 0.25 * log(patch_experts.patch_scaling[scale_max]/0.25)/log(2);
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tmp_parameters.weight_factor = parameters.weight_factor + 2 * parameters.weight_factor * log(patch_experts.patch_scaling[scale_max]/0.25)/log(2);
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}
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// Get the current landmark locations
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