Budhaditya Goswami

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—Lip region deformation during speech contains bio-metric information and is termed visual speech. This biometric information can be interpreted as being genetic or behavioural depending on whether static or dynamic features are extracted. In this paper, we use a texture descriptor called Local Ordinal Contrast Pattern (LOCP) with a dynamic texture(More)
The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic(More)
The lip-region can be interpreted as either a genetic or behavioural biometric trait depending on whether static or dynamic information is used. In this paper, we use a texture descriptor called Local Ordinal Contrast Pattern (LOCP) in conjunction with a novel spatiotem-poral sampling method called Windowed Three Orthogonal Planes (WTOP) to represent both(More)
The lip-region can be interpreted as either a genetic or behavioural biometric trait. Despite this breadth of biometric content, lip-based biometric systems are scarcely developed in the literature. A recent trend in lip biometrics is to use a spatiotemporal texture representation of visual speech to generate biometric features. In this paper we make two(More)
This research aims to develop a methodological framework based on a data driven approach known as particle filters, often found in computer vision methods, to correct the effect of respiratory motion on Nuclear Medicine imaging data. Particles filters are a popular class of numerical methods for solving optimal estimation problems and we wish to use their(More)
Automatic lip segmentation is an indispensable prerequisite in face-video applications that make use of the mouth-region. Lip segmentation can be treated as a three-stage process: mouth-region detection , separation of the constituent clusters in this region and identification of the cluster containing the lip pixels. This paper describes a novel method of(More)
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