3D shape extraction of human face in presence of facial hair: A profilometric approach

The increasing use of 3D modeling of Human Face in Face Recognition systems, User Interfaces, Graphics, Gaming and the like has made it an area of active study. Majority of the 3D sensors rely on color coded light projection for 3D estimation. Such systems fail to generate any response in regions covered by Facial Hair (like beard, mustache), and hence generate holes in the model which have to be filled manually later on. We propose the use of wavelet transform based analysis to extract the 3D model of Human Faces from a sinusoidal white light fringe projected image. Our method requires only a single image as input. The method is robust to texture variations on the face due to space-frequency localization property of the wavelet transform. It can generate models to pixel level refinement as the phase is estimated for each pixel by a continuous wavelet transform. In cases of sparse Facial Hair, the shape distortions due to hairs can be filtered out, yielding an estimate for the underlying face. We use a low-pass filtering approach to estimate the face texture from the same image. We demonstrate the method on several Human Faces both with and without Facial Hairs. Unseen views of the face are generated by texture mapping on different rotations of the obtained 3D structure. To the best of our knowledge, this is the first attempt to estimate 3D for Human Faces in presence of Facial hair structures like beard and mustache without generating holes in those areas.

A neuro-adaptive augmented optimal dynamic inversion approach for effective and efficient treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.

Molecular structure-activity relationship study of some non-steroidal antiinflammatory agents using electrostatic potential mapping

A series of 6,11-dihydro-11-oxodibenz[b,e]oxepin-2-acetic acids (DOAA) which are known to be anti-inflammatory agents were studied. The geometries of some of the molecules obtained from X-ray crystallography were used in the calculations as such while the geometries of their derivatives were obtained by local, partial geometry optimization around the Sites of substitution employing the AMI method, keeping the remaining parts of the geometries the same as those in the parent molecules. Molecular electrostatic potential (MEP) mapping was performed for the molecules using optimized hybridization displacement charges (HDC) combined with Lowdin charges, as this charge distribution has been shown earlier to yield near ab initio quality results. A good correlation has been found between the MEP values near the oxygen atoms of the hydroxyl groups of the carboxy groups of the molecules and their anti-inflammatory activities. The result is broadly in agreement with the model proposed earlier by other authors regarding the structure-activity relationship for other similar molecules.

Physical mapping of the genomic DNA of the Oryctes rhinoceros baculovirus, KI

A non-occluded baculovirus, OBV-KI has been isolated from the insect pest, Oryctes rhinoceros. The viral genome is estimated to be 123 kb, with a G + C content of 43 mol% and no detectible methylated bases. A restriction map of the OBV-KI genome for BamHI, EcoRI, HindIII, PstI, SalI and XbaI has been constructed.

Novel gray coded pattern for unwrapping phase in fringe projection based 3D profiling

A method to reliably extract object profiles even with height discontinuities (that leads to 2n pi phase jumps) is proposed. This method uses Fourier transform profilometry to extract wrapped phase, and an additional image formed by illuminating the object of interest by a novel gray coded pattern for phase unwrapping. Simulation results suggest that the proposed approach not only retains the advantages of the original method, but also contributes significantly in the enhancement of its performance. Fundamental advantage of this method stems from the fact that both extraction of wrapped phase and unwrapping the same were done by gray scale images. Hence, unlike the methods that use colors, proposed method doesn't demand a color CCD camera and is ideal for profiling objects with multiple colors.

Measurement of complex optical flow with use of an augmented generalized gradient scheme

We present a method for measuring the local velocities and first-order variations in velocities in a timevarying image. The scheme is an extension of the generalized gradient model that encompasses the local variation of velocity within a local patch of the image. Motion within a patch is analyzed in parallel by 42 different spatiotemporal filters derived from 6 linearly independent spatiotemporal kernels. No constraints are imposed on the image structure, and there is no need for smoothness constraints on the velocity field. The aperture problem does not arise so long as there is some two-dimensional structure in the patch being analyzed. Among the advantages of the scheme is that there is no requirement to calculate second or higher derivatives of the image function. This makes the scheme robust in the presence of noise. The spatiotemporal kernels are of simple form, involving Gaussian functions, and are biologically plausible receptive fields. The validity of the scheme is demonstrated by application to both synthetic and real video images sequences and by direct comparison with another recently published scheme Biol. Cybern. 63, 185 (1990)] for the measurement of complex optical flow.

Measurement of complex optical flow with use of an augmented generalized gradient scheme

We present a method for measuring the local velocities and first-order variations in velocities in a time-varying image. The scheme is an extension of the generalized gradient model that encompasses the local variation of velocity within a local patch of the image. Motion within a patch is analyzed in parallel by 42 different spatiotemporal filters derived from 6 linearly independent spatiotemporal kernels. No constraints are imposed on the image structure, and there is no need for smoothness constraints on the velocity field. The aperture problem does not arise so long as there is some two-dimensional structure in the patch being analyzed. Among the advantages of the scheme is that there is no requirement to calculate second or higher derivatives of the image function. This makes the scheme robust in the presence of noise. The spatiotemporal kernels are of simple form, involving Gaussian functions, and are biologically plausible receptive fields. The validity of the scheme is demonstrated by application to both synthetic and real video images sequences and by direct comparison with another recently published scheme [Biol. Cybern. 63, 185 (1990)] for the measurement of complex optical flow.

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

A novel method for mapping assembled epitopes in batches: Identification of three epitopes at the receptor binding region of human chorionic gonadotropin

Identification of conformation-specific epitopes of hCG beta has been done using a simple batch method, Chemically or enzymatically-modified hCG beta has been prepared in a batch and the effect of modifications on the integrity of different epitope regions has been investigated in a quantitative manner using monoclonal antibodies (MAbs) immobilized on plastic tubes from culture supernatants. Based on the extent of damage done to different regions by different modifications, three conformation-specific epitopes of hCG beta have been identified. The method has been shown to have important advantages over the existing methods on many considerations, Using this approach, these epitopes have been shown to be at/near the receptor-binding region.

Antigenic determinants at the carboxy terminus of chicken egg white riboflavin carrier protein (RCP): Epitope mapping and antibody-mediated pregnancy curtailment in rodents

The epitopic core sequences recognized by three monoclonal antibodies raised to chicken riboflavin carrier protein (RCP) were mapped to the C-terminal tail-end of the protein using the pepscan method A 21-residue synthetic peptide corresponding to residues 200-219 of the protein and comprising the regions corresponding to the antibodies was synthesized. Administration of polyclonal antibodies specific to this peptide led to termination of early pregnancy in mice. Also, active immunization of rats with the peptide-purified protein derivative conjugate inhibited establishment of pregnancy. These results demonstrate the functional importance of the C-terminal 200-219 region of chicken RCP. Copyright (C) 1996 Elsevier Science Ltd.

RS and GIS in mapping of geomorphic records and understanding the local controls of glacial retreat from the Baspa Valley, Himachal Pradesh, India

We report here the role of remote sensing (RS) and geographical information system (GIS) in the identification of geomorphic records and understanding of the local controls on the retreat of glaciers of the Baspa Valley, Himachal Pradesh, India. The geomorphic records mapped are accumulation zone, exposed ablation zone, moraine-covered ablation zone, snout, deglaciated valley, lateral moraine, medial moraine, terminal moraine and hanging glacier. Details of these features and stages of deglaciation have been extracted from RS data and mapped in a GIS environment. Glacial geomorphic data have been generated for 22 glaciers of the Baspa Valley. The retreat of glaciers has been estimated using the glacial maxima observed on satellite images. On the basis of percentage of retreat and the critical analysis of glacial geomorphic data for 22 glaciers of the Baspa Valley, they are classified into seven categories of very low to very very high retreat. From the analysis of the above 22 glaciers, it has been found that other than global warming, the retreat of glaciers of the Baspa Valley is inversely proportional to the size of the accumulation zone and the ratio of the moraine covered ablation/exposed ablation zone.

Mapping adaptive resonance theory onto ring and mesh architectures

In recent years, parallel computers have been attracting attention for simulating artificial neural networks (ANN). This is due to the inherent parallelism in ANN. This work is aimed at studying ways of parallelizing adaptive resonance theory (ART), a popular neural network algorithm. The core computations of ART are separated and different strategies of parallelizing ART are discussed. We present mapping strategies for ART 2-A neural network onto ring and mesh architectures. The required parallel architecture is simulated using a parallel architectural simulator, PROTEUS and parallel programs are written using a superset of C for the algorithms presented. A simulation-based scalability study of the algorithm-architecture match is carried out. The various overheads are identified in order to suggest ways of improving the performance. Our main objective is to find out the performance of the ART2-A network on different parallel architectures. (C) 1999 Elsevier Science B.V. All rights reserved.

Mapping of B-cell epitopes of hemagglutinin protein of rinderpest virus

Monoclonal antibodies (mAbs) against secreted hemagglutinin (H) protein of rinderpest virus (RPV) expressed by a recombinant baculovirus were generated to characterize the antigenic sites on H protein and regions of functional significance. Three of the mAbs displayed hemagglutination inhibition activity and these mAbs were unable to neutralize virus infectivity. Western immunoblot analysis of overlapping deletion mutants indicated that three mAbs recognize antigenic regions at the extreme carboxy terminus (between amino acids 569 and 609) and the fourth mAb between amino acids 512 and 568. Using synthetic peptides, aa 569-577 and 575-583 were identified as the epitopes for E2G4 and D2F4, respectively. The epitopic domains of A12A9 and E2B6 mAbs were mapped to regions encompassing aa 527-554 and 588-609. Two epitopes spanning the extreme carboxy terminal region of aa 573 to 587 and 588 to 609 were shown to be immunodominant employing a competitive ELISA with polyclonal sera form vaccinated cattle. The D2F4 mAb which recognizes a unique epitope on RPV-H is not present on the closely related peste des petits ruminant virus FIN protein and this mAb could serve as a tool in the seromonitoring program after rinderpest vaccination. (C) 2002 Elsevier Science (USA).

The restriction mapping problem revisited

In computational molecular biology, the aim of restriction mapping is to locate the restriction sites of a given enzyme on a DNA molecule. Double digest and partial digest are two well-studied techniques for restriction mapping. While double digest is NP-complete, there is no known polynomial-time algorithm for partial digest. Another disadvantage of the above techniques is that there can be multiple solutions for reconstruction. In this paper, we study a simple technique called labeled partial digest for restriction mapping. We give a fast polynomial time (O(n(2) log n) worst-case) algorithm for finding all the n sites of a DNA molecule using this technique. An important advantage of the algorithm is the unique reconstruction of the DNA molecule from the digest. The technique is also robust in handling errors in fragment lengths which arises in the laboratory. We give a robust O(n(4)) worst-case algorithm that can provably tolerate an absolute error of O(Delta/n) (where Delta is the minimum inter-site distance), while giving a unique reconstruction. We test our theoretical results by simulating the performance of the algorithm on a real DNA molecule. Motivated by the similarity to the labeled partial digest problem, we address a related problem of interest-the de novo peptide sequencing problem (ACM-SIAM Symposium on Discrete Algorithms (SODA), 2000, pp. 389-398), which arises in the reconstruction of the peptide sequence of a protein molecule. We give a simple and efficient algorithm for the problem without using dynamic programming. The algorithm runs in time O(k log k), where k is the number of ions and is an improvement over the algorithm in Chen et al. (C) 2002 Elsevier Science (USA). All rights reserved.