Pawar M.,Instruments Research and Development Establishment
2012 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2012 | Year: 2012
Mean shift based face tracking is able to track face nicely under controlled conditions. It usually fails when there is noise and rapid illumination variations over face. The main reason for failure is that mean shift employs fixed histogram based target model representation. In this paper we present a novel technique of continuously updating the target model histogram for more robust mean shift based face tracking using a Bayesian skin classifier. We used Bayesian skin classifier to learn new skin color features from face templates in successive frames. The classifier use likelihood ratio for extracting new skin color features from each new face template. The Bayesian skin classifier had been used mainly for detection of skin parts in images but we extend this idea to continuously update the target model histogram with learned features to accommodate the dynamics of pose change and illumination in a video sequence for more robust face tracking. © 2012 IEEE.
Negi R.,Instruments Research and Development Establishment
Proceedings 12th International Conference on Fiber Optics and Photonics, Photonics 2014 | Year: 2014
This paper presents a novel technique to design complex periodic pattern for the 2D photonic crystal using Talbot self-imaging.The plane wave simulation in RSoft software exhibits photonic bandgaps for these 2D periodic structures. © OSA 2014.
Bartlett A.P.,Memorial University of Newfoundland |
Bartlett A.P.,McMaster University |
Agarwal A.K.,Memorial University of Newfoundland |
Agarwal A.K.,Instruments Research and Development Establishment |
Yethiraj A.,Memorial University of Newfoundland
Langmuir | Year: 2011
Order-disorder transitions in colloidal systems are an attractive option for making switchable materials. Electric-field-driven order-disorder transitions are especially attractive for this purpose because the tuning parameter is easily and externally controllable. However, precise positional control of 3D structure is immensely challenging. Using patterned electrodes, we demonstrate that ac electric fields - dominantly dielectrophoresis (DEP) coupled with an electrohydrodynamic mechanism consisting of induced-charge electro-osmosis (ICEO) - can be used to template colloidal order dynamically in three dimensions. We find that the electric field geometry dictates the location, size, and shape of colloidal patterns and can produce patterns with surprising complexity. © 2011 American Chemical Society.
Gupta A.K.,Indian Institute of Technology Roorkee |
Harsha S.P.,Instruments Research and Development Establishment
Nano | Year: 2015
In this paper, a multiscale modeling approach is proposed for studying the pinhole defects in double wall carbon nanotube (DWNT) reinforced polymer composites. Two configurations of DWNT i.e., armchair (5,5), (10,10) and zigzag (9,0), (16,0) are selected for the analyses wherein C-C bonds at atomic scale are modeled as Euler beam. The three-dimensional (3D) solid elements are used for matrix material and square representative volume element (RVE) is constructed for the nanocomposite. These composite materials consist of aligned carbon nanotubes (CNTs) that are uniformly distributed within the matrix. The presence of chemical covalent bonding between functionalized CNT and matrix are modeled as elastic crosslinks. The nonbonded van der Waals interactions between inner and outer wall are modeled as cohesive interaction elements. The influence of the pinhole defects on the nanocomposite are studied under axial load condition. It has been observed that with the increase in the number of atomic vacancies, the elastic modulus of the composite are reduced significantly. The effects of nanotube chirality and composite stiffness ratio on the elastic properties are also analyzed in the presence of pinhole defects. © 2015 World Scientific Publishing Company.
Kumar A.,Instruments Research and Development Establishment
Defence Science Journal | Year: 2013
The advancement in infrared (IR) detector technologies from 1st to 3rd generation and beyond has resulted in the improvement of infrared imaging systems due to availability of IR detectors with large number of pixels, smaller pitch, higher sensitivity and large F-number. However, it also results in several problems and most serious of them is sensor non-uniformities, which are mainly attributed to the difference in the photo-response of each detector in the infrared focal plane array. These spatial and temporal non-uniformities result in a slowly varying pattern on the image usually called as fixed pattern noise and results in the degradation the temperature resolving capabilities of thermal imaging system considerably. This paper describes two types of non uniformity correction methodologies. First type of algorithms deals with correction of sensor non-uniformities based upon the calibration method. Second type of algorithm deals with correction of sensor non uniformities using scene information present in the acquired images. The proposed algorithms correct both additive and multiplicative non uniformities. These algorithms are evaluated using the simulated & actual infrared data and results of implementations are presented. Furthermore, proposed algorithms are implemented in field programmable gate array based embedded hardware. © 2013, DESIDOC.