Aurobinda Routray

TL;DR: An automated learning-free facial landmark detection technique has been proposed, which achieves similar performances as that of other state-of-art landmark detection methods, yet requires significantly less execution time.

TL;DR: It has been found that the proposed algorithm is suitable for real-time applications especially when the frequency changes are abrupt and the signal is corrupted with noise and other disturbances due to harmonics.

TL;DR: In this article, a few prominent facial patches, depending on the position of facial landmarks, are extracted which are active during emotion elicitation, and these active patches are further processed to obtain the salient patches which contain discriminative features for classification of each pair of expressions, thereby selecting different facial patches as salient for different pair of expression classes.

TL;DR: In this article, a least mean square (LMS) algorithm in complex form is presented to estimate power system frequency where the formulated structure is very simple and the three-phase voltages are converted to a complex form for processing by the proposed algorithm.

TL;DR: A method based on a class of entropy measures on the recorded EEG signals of human subjects for relative quantification of fatigue during driving and results show definite patterns of these entropies during different stages of fatigue.