sustaining_gazes/matlab_runners/Action Unit Experiments/results/DISFA_valid_res_back.txt

AU1 results - corr 0.832, rms 0.405, ccc - 0.809
AU2 results - corr 0.763, rms 0.445, ccc - 0.658
AU4 results - corr 0.863, rms 0.583, ccc - 0.838
AU5 results - corr 0.750, rms 0.179, ccc - 0.720
AU6 results - corr 0.702, rms 0.604, ccc - 0.657
AU9 results - corr 0.745, rms 0.382, ccc - 0.690
AU12 results - corr 0.865, rms 0.510, ccc - 0.850
AU15 results - corr 0.753, rms 0.264, ccc - 0.717
AU17 results - corr 0.656, rms 0.499, ccc - 0.589
AU20 results - corr 0.633, rms 0.305, ccc - 0.589
AU25 results - corr 0.914, rms 0.543, ccc - 0.903
AU26 results - corr 0.805, rms 0.447, ccc - 0.763
A lot of changes: - New AU recognition models trained on extra datasets - Bosphorus, UNBC, FERA2011 - Cleaner and clearer separation of static and dynamic AU models - AU training code cleaned up and instructions added - bug fixes with median feature computation - AU prediction correction (smoothing and shifting) with post processing 2016-07-22 13:35:50 +00:00			`AU1 results - corr 0.832, rms 0.405, ccc - 0.809`
			`AU2 results - corr 0.763, rms 0.445, ccc - 0.658`
			`AU4 results - corr 0.863, rms 0.583, ccc - 0.838`
			`AU5 results - corr 0.750, rms 0.179, ccc - 0.720`
			`AU6 results - corr 0.702, rms 0.604, ccc - 0.657`
			`AU9 results - corr 0.745, rms 0.382, ccc - 0.690`
			`AU12 results - corr 0.865, rms 0.510, ccc - 0.850`
			`AU15 results - corr 0.753, rms 0.264, ccc - 0.717`
			`AU17 results - corr 0.656, rms 0.499, ccc - 0.589`
			`AU20 results - corr 0.633, rms 0.305, ccc - 0.589`
			`AU25 results - corr 0.914, rms 0.543, ccc - 0.903`
			`AU26 results - corr 0.805, rms 0.447, ccc - 0.763`