Pavel Bhowmik

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Facial expressions of a person representing similar emotion are not always unique. Naturally, the facial features of a subject taken from different instances of the same emotion have wide variations. In the presence of two or more facial features, the variation of the attributes together makes the emotion recognition problem more complicated. This variation(More)
Memetic algorithms (MAs) are population-based meta-heuristic search algorithms that combine the composite benefits of natural and cultural evolutions. An adaptive MA (AMA) incorporates an adaptive selection of memes (units of cultural transmission) from a meme pool to improve the cultural characteristics of the individual member of a population-based search(More)
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three(More)
The paper employs Lagrange's mean value theorem of differential Calculus to design a new strategy for the selection of parameter vectors in the Differential Evolution (DE) algorithm. Classical differential evolution selects parameter vectors randomly to obtain the donor vectors. These donor vectors thus cannot be directly used as trial solution to the(More)
Memetic algorithms are population-based meta-heuristic search algorithms that combine the composite benefits of natural and cultural evolution. In this paper a synergism of the classical Differential Evolution algorithm and Q-learning is used to construct the memetic algorithm. Computer simulation with standard benchmark functions reveals that the proposed(More)
Manifestation of a given emotion on facial expression is not always unique, as the facial attributes in different instances of similar emotional experiences may vary widely. When a number of facial attributes are used to recognize the emotion of a subject, the variation of individual attributes together makes the problem more complicated. This variation is(More)
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three(More)
Determining correlation between aroused emotion and its manifestation on facial expression, voice, gesture and posture have interesting applications in psychotherapy. A set of audiovisual stimulus, selected by a group of experts, is used to excite emotion of the subjects. EEG and facial expression of the subjects excited by the selected audio-visual(More)
The paper provides a new direction to controlling psychological balance in emotion-logic encounter. A dynamics of co-existing multiple emotions is considered, and the condition for stability of the dynamics is determined by Lyapunov approach. Stabilization of the emotional dynamics is ascertained through Hebbian learning by autonomous adaptation of(More)