Rizwan Ahmed Khan

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Automatic recognition of facial expressions is a challenging problem specially for low spatial resolution facial images. It has many potential applications in human–computer interactio ns, social robots, deceit detection, interactive video and behavior monitoring. In this study we present a nov el frame work that can recognize facial expressions very(More)
We present a novel human vision inspired framework that can recognize facial expressions very efficiently and accurately. We propose to computationally process small, salient region of the face to extract features as it happens in human vision. To determine which facial region(s) is perceptually salient for a particular expression, we conducted a(More)
This paper focus on understanding human visual system when it decodes or recognizes facial expressions. Results presented can be exploited by the computer vision research community for the development of robust descriptor based on human visual system for facial expressions recognition. We have conducted psycho-visual experimental study to find which facial(More)
In this paper we are proposing a novel computer vision system that can recognize expression of pain in videos by analyzing facial features. Usually pain is reported and recorded manually and thus carry lot of subjectivity. Manual monitoring of pain makes difficult for the medical practitioners to respond quickly in critical situations. Thus, it is desirable(More)
Detection of visual saliency is of great interest for a lot of computer vision applications in particular for content-based image retrieval. The work presented in this paper is devoted to develop an algorithm of saliency detection that performs adequately in predicting human fixations for stimuli containing blur and sharp regions. This work is based on an(More)
—This paper proposes a novel framework for universal facial expression recognition. The framework is based on two sets of features extracted from the face image: en-tropy and brightness. First, saliency maps are obtained by state-of-the-art saliency detection algorithm i.e. " frequency-tuned salient region detection ". Then only localized salient facial(More)