M. Umair Bin Altaf

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We describe the acoustic gaits-the natural human gait quantitative characteristics derived from the sound of footsteps as the person walks normally. We introduce the acoustic gait profile, which is obtained from temporal signal analysis of sound of footsteps collected by microphones and illustrate some of the spatio-temporal gait parameters that can be(More)
Human identification using unobtrusive methods is a challenging problem that has many applications in surveillance tasks. In this work we propose a set of biometric features extracted from a footstep audio signal that can be used to identify a person. Instead of using short-time spectral domain, Teager-Kaiser energy operator is employed to transform a(More)
The conventional approach to audio processing, based on the short-time power spectrum model, is not adequate when it comes to general audio signals. We propose an approach, justified by studies from psycho-acoustics and neuroimaging, which uses the magnitude and frequency envelope of the audio signal in the from of AM-FM modulations to build an ARMA model(More)
Real world sounds are ubiquitous and form an important part of the edifice of our cognitive abilities. Their perception combines signatures from spectral and temporal domains, among others, yet traditionally their analysis is focused on the frame based spectral properties. We consider the problem of sound analysis from perceptual perspective and investigate(More)
In this dynamic global environment only those companies survive who know the power of knowledge and consistently create new knowledge. Such knowledge creating firms utilize dynamic dimensions of human capital. Human capital is the most important resource for a firm and has ability to create new knowledge in a changing environment. Various dimensions of(More)
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