Dipan K. Pal

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A lot of real-world data is spread across multiple domains. Handling such data has been a challenging task. Heterogeneous face biometrics has begun to receive attention in recent years. In real-world scenarios, many surveillance cameras capture data in the NIR (near infrared) spectrum. However, most datasets accessible to law enforcement have been collected(More)
  • Dipan K. Pal
  • Journal of epidemiology and community health
  • 1996
STUDY OBJECTIVE To clarify concepts and methodological problems in existing multidimensional health status measures for children. DESIGN Thematic review of instruments found by computerised and manual searches, 1979-95. SUBJECTS Nine health status instruments. MAIN RESULTS Many instruments did not satisfy criteria of being child centered or family(More)
A proto-type space-based disaster management system (DMS) has been organized with comprehensive database design, space-based near real-time monitoring/mapping tools, modelling framework, networking solutions and multi-agency interfaces. With the appropriate synthesis of these core elements, a systemdefinition of the frame-work of a DMS has been arrived at,(More)
Identifying a suspect wearing a mask (where only the suspect's periocular region is visible) is one of the toughest real-world challenges in biometrics that exist. In this paper, we present a practical method to hallucinate the full frontal face given only the periocular region of a face. This is an important problem faced in many law-enforcement(More)
The harmful effects of cell phone usage on driver behavior have been well investigated and the growing problem has motivated several several research efforts aimed at developing automated cell phone usage detection systems. Computer vision based approaches for dealing with this problem have only emerged in recent years. In this paper, we present a vision(More)
Modern day law enforcement banks heavily on the use of commercial off-the-shelf (COTS) face recognition systems (FRS) as a tool for biometric evaluation and identification. However, in many real-world scenarios, when the face of an individual is occluded or degraded in some way, commercial recognition systems fail to accept the face for evaluation or simply(More)
The search for new biometrics is never ending. In this work, we investigate the use of image based nasal features as a biometric. In many real-world recognition scenarios, partial occlusions on the face leave the nose region visible (e.g. sunglasses). Face recognition systems often fail or perform poorly in such settings. Furthermore, the nose region(More)
We propose an explicitly discriminative and 'simple' approach to generate invariance to nuisance transformations modeled as unitary. In practice, the approach works well to handle non-unitary transformations as well. Our theoretical results extend the reach of a recent theory of invariance to discriminative and kernelized features based on unitary kernels.(More)
In this paper, we formulate the K-sparse compressed signal recovery problem with the L0 norm within a Stochastic Local Search (SLS) framework. Using this randomized framework, we generalize the popular sparse recovery algorithm CoSaMP, creating Stochastic CoSaMP (StoCoSaMP). Interestingly, our deterministic worst case analysis shows that under the(More)
Many optimization problems are multi-modal. In certain cases, we are interested in finding multiple locally optimal solutions rather than just a single optimum as is computed by traditional genetic algorithms (GAs). Several niching techniques have been developed that seek to find multiple such local optima. These techniques, which include sharing and(More)