Subspace Representations for Robust Face and Facial Expression Recognition

Analyzing human faces and modeling their variations have always been of interest to the computer vision community. Face analysis based on 2D intensity images is a challenging problem, complicated by variations in pose, lighting, blur, and non-rigid facial deformations due to facial expressions. Among the different sources of variation, facial expressions are of interest as important channels of non-verbal communication. Facial expression analysis is also affected by changes in view-point and inter-subject variations in performing different expressions. This dissertation makes an attempt to address some of the challenges involved in developing robust algorithms for face and facial expression recognition by exploiting the idea of proper subspace representations for data. Variations in the visual appearance of an object mostly arise due to changes in illumination and pose. So we first present a video-based sequential algorithm for estimating the face albedo as an illumination-insensitive signature for face recognition. We show that by knowing/estimating the pose of the face at each frame of a sequence, the albedo can be efficiently estimated using a Kalman filter. Then we extend this to the case of unknown pose by simultaneously tracking the pose as well as updating the albedo through an efficient Bayesian inference method performed using a Rao-Blackwellized particle filter. Since understanding the effects of blur, especially motion blur, is an important problem in unconstrained visual analysis, we then propose a blur-robust recognition algorithm for faces with spatially varying blur. We model a blurred face as a weighted average of geometrically transformed instances of its clean face. We then build a matrix, for each gallery face, whose column space spans the space of all the motion blurred images obtained from the clean face. This matrix representation is then used to define a proper objective function and perform blur-robust face recognition. To develop robust and generalizable models for expression analysis one needs to break the dependence of the models on the choice of the coordinate frame of the camera. To this end, we build models for expressions on the affine shape-space (Grassmann manifold), as an approximation to the projective shape-space, by using a Riemannian interpretation of deformations that facial expressions cause on different parts of the face. This representation enables us to perform various expression analysis and recognition algorithms without the need for pose normalization as a preprocessing step. There is a large degree of inter-subject variations in performing various expressions. This poses an important challenge on developing robust facial expression recognition algorithms. To address this challenge, we propose a dictionary-based approach for facial expression analysis by decomposing expressions in terms of action units (AUs). First, we construct an AU-dictionary using domain experts' knowledge of AUs. To incorporate the high-level knowledge regarding expression decomposition and AUs, we then perform structure-preserving sparse coding by imposing two layers of grouping over AU-dictionary atoms as well as over the test image matrix columns. We use the computed sparse code matrix for each expressive face to perform expression decomposition and recognition. Most of the existing methods for the recognition of faces and expressions consider either the expression-invariant face recognition problem or the identity-independent facial expression recognition problem. We propose joint face and facial expression recognition using a dictionary-based component separation algorithm (DCS). In this approach, the given expressive face is viewed as a superposition of a neutral face component with a facial expression component, which is sparse with respect to the whole image. This assumption leads to a dictionary-based component separation algorithm, which benefits from the idea of sparsity and morphological diversity. The DCS algorithm uses the data-driven dictionaries to decompose an expressive test face into its constituent components. The sparse codes we obtain as a result of this decomposition are then used for joint face and expression recognition

Level-set segmentation of brain tumors in magnetic resonance images

Master'sMASTER OF ENGINEERIN

Phenotypic and molecular effects of chronic gamma irradiation on Curcuma alismatifolia

Mutation breeding is one of the methods for generating genetic variation and obtaining new cultivars of ornamental plants during the past decades. In present study, the effects of four doses (0, 14.6, 33, and 87.4 Gy) of chronic gamma irradiation on three cultivars of Curcuma alismatifolia and one Curcuma hybrid were investigated. Morphological aberrations from non-treated plants were observed by exposing growing plants. Higher doses induced phenotypical variations and significantly affected the plant growth parameters and flowering capacity. In terms of genetic variation, among the irradiated cultivars, the number of presumed alleles revealed by SSR analysis ranged from two to five with a mean value of 3.1 to 3.7 alleles per locus for radiation doses. The average value of the effective number of alleles, Nei’s gene diversity, and Shannon’s information index were 2.42–2.66, 0.50–0.56, and 0.90–1.03, respectively. Heat map hierarchical clustering divided 52 studied individuals into four major clusters. Results of this study showed that chronic gamma irradiation efficiently can enhance the phenotypical and genetic variations in C. alismatifolia cultivars at doses of 33 Gy and 84.6 Gy. In addition, SSR markers will likely accelerate the progress of selection of desired mutants during mutation breeding programs

Antioxidant capacities and total phenolic contents enhancement with acute gamma irradiation in Curcuma alismatifolia (Zingiberaceae) leaves

The present study was conducted in order to assess the effect of various doses of acute gamma irradiation (0, 10, 15, and 20 Gy) on the improvement of bioactive compounds and their antioxidant properties of Curcuma alismatifolia var. Sweet pink. The high performance liquid chromatography (HPLC) and gas chromatography (GC) analysis uncovered that various types of phenolic, flavonoid compounds, and fatty acids gradually altered in response to radiation doses. On the other hand, antioxidant activities determined by 1,1-Diphenyl-2-picryl-hydrazyl (DPPH), ferric reduction, antioxidant power (FRAP), and 2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging assay showed a higher irradiation level significantly increased the antioxidant properties. This study revealed an efficient effect of varying levels of gamma radiation, based on the pharmaceutical demand to enhance the accumulation and distribution of bioactive compounds such as phenolic and flavonoid compounds, fatty acids, as well as their antioxidant activities in the leaves of C. alismatifolia var. Sweet pink

Evaluating system of rice intensification using a modified transplanter: A smart farming solution toward sustainability of paddy fields in Malaysia

This paper presents the study reports on evaluating a new transplanting operation by taking into accounts the interactions between soil, plant, and machine in line with the System of Rice Intensification (SRI) practices. The objective was to modify planting claw (kuku-kambing) of a paddy transplanter in compliance with SRI guidelines to determine the best planting spacing (S), seed rate (G) and planting pattern that results in a maximum number of seedling, tillers per hill, and yield. Two separate experiments were carried out in two different paddy fields, one to determine the best planting spacing (S=4 levels: s1=0.16 m×0.3 m, s2= 0.18 m×0.3 m, s3=0.21 m×0.3 m, and s4=0.24 m×0.3 m) for a specific planting pattern (row mat or scattered planting pattern), and the other to determine the best combination of spacing with seed rate treatments (G=2 levels: g1=75 g/tray, and g2= 240 g/tray). Main SRI management practices such as soil characteristics of the sites, planting depth, missing hill, hill population, the number of seedling per hill, and yield components were evaluated. Results of two-way analysis of variance with three replications showed that spacing, planting pattern and seed rate affected the number of one-seedling in all experiment. It was also observed that the increase in spacing resulted in more tillers and more panicle per plant, however hill population and sterility ratio increased with the decrease in spacing. While the maximum number of panicles were resulted from scattered planting at s4=0.24 m×0.3 m spacing with the seed rate of g1=75 g/tray, the maximum number of one seedling were observed at s4=0.16 m×0.3 m. The highest and lowest yields were obtained from 75 g seeds per tray scattered and 70 g seeds per tray scattered treatment respectively. For all treatments, the result clearly indicates an increase in yield with an increase in spacing.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

TILLING, high-resolution melting (HRM), and next-generation sequencing (NGS) techniques in plant mutation breeding

Induced mutations have been used effectively for plant improvement. Physical and chemical mutagens induce a high frequency of genome variation. Recently, developed screening methods have allowed the detection of single nucleotide polymorphisms (SNPs) and the identification of traits that are difficult to identify at the molecular level by conventional breeding. With the assistance of reverse genetic techniques, sequence variation information can be linked to traits to investigate gene function. Targeting induced local lesions in genomes (TILLING) is a high-throughput technique to identify single nucleotide mutations in a specific region of a gene of interest with a powerful detection method resulted from chemical-induced mutagenesis. The main advantage of TILLING as a reverse genetics strategy is that it can be applied to any species, regardless of genome size and ploidy level. However, TILLING requires laborious and time-consuming steps, and a lack of complete genome sequence information for many crop species has slowed the development of suitable TILLING targets. Another method, high-resolution melting (HRM), which has assisted TILLING in mutation detection, is faster, simpler and less expensive with non-enzymatic screening system. Currently, the sequencing of crop genomes has completely changed our vision and interpretation of genome organization and evolution. Impressive progress in next-generation sequencing (NGS) technologies has paved the way for the detection and exploitation of genetic variation in a given DNA or RNA molecule. This review discusses the applications of TILLING in combination with HRM and NGS technologies for screening of induced mutations and discovering SNPs in mutation breeding programs.Peer reviewe

Flower ontogenesis and fruit development of Synsepalum dulcificum

Synsepalum dulcificum from the family Sapotaceae is known as miracle fruit and is a valuable horticultural species. All plant parts are of medicinal importance whereas the fruit known as magic berry, miracle berry, or sweet berry is consumed fresh. Surprisingly, very little is known on the species in terms of flower morphology and flower development. In this study, an observation on the flower morphology and flower development of miracle fruit has been made with the aid of microscopic techniques. Miracle fruit flower requires 100 days to develop from reproductive meristem to full anthesis. The flower development can be divided into six stages based on the size and appearance of the flower bud. The fruit with persistent style developed and ripened 90 days after anthesis. Heavy fruit drop was observed at 40–60 days after anthesis which contributed to the final fruit set of average of 5.06% per plant. Through this study, miracle fruit is strongly insect pollinated and prevents self-fertilization. A study on pollination ecology is needed to identify the pollinator for miracle fruit, as this is important in manipulating fruit loading in the future

Application of high resolution melting for detection of induced DNA polymorphism in Curcuma alismatifolia

In order to reveal the induced variations in genomic DNA of mutants, simple sequence repeats (SSR) are used in plant genetics and breeding programs, which are commonly analyzed by fragment size separation using gel electrophoresis. However, post-PCR handling processes are laborious and costly. In addition, gel electrophoresis based methods cannot detect SNPs present in the sequences flanking repeat motif. High resolution melting curve (HRM) analysis is a new technique, which is efficient, accurate, and cost-effective in detecting the sequence differences in polymerase chain reaction (PCR) amplicons, even single nucleotide polymorphisms (SNPs) or insertions or deletions (INDELs). In present study, we used the HRM followed by DNA sequencing to discriminate induced microsatellite polymorphism among irradiated and non-irradiated individuals of Curcuma alismatifolia in third generation (M1V1). The results showed that the combination of HRM with sequence confirmation is a powerful high-throughput, accurate, and reproducible approach to detect induced SSR polymorphism among mutants of C. alismatifolia. For the mutants with SNPs polymorphism present in the flanking region, HRM also gave distinct melting curves, which the gel electrophoresis was not able to detect. In conclusion, it has been approved that HRM as pre-sequencing, efficient, and cost-effective screening method enables rapid SSR polymorphism detection in mutant population of C. alismatifolia

BIOTECHNOLOGICAL PRODUCTS AND PROCESS ENGINEERING EGFP reporter protein: its immunogenicity in Leishmania-infected BALB/c mice

Abstract Optical reporter genes such as green fluorescent protein (GFP) and luciferase are efficiently and widely used in monitoring and studying the protective/therapeutic potential of candidate agents in leishmaniasis. But several observations and controversial reports have generated a main concern, whether enhanced GFP (EGFP) affects immune response. To address this issue, we studied the immunogenicity of EGFP in vivo by two lines of stably transfected parasites (Leishmania major EGFP or L. major EGFP-LUC ) in BALB/c model and/or as a recombinant protein (rEGFP) produced in vitro by bacteria in parallel. Disease progression was followed by footpad swelling measurements and parasite burden in draining lymph nodes using microtitration assay and real-time PCR, and immune responses were also evaluated in spleen. EGFP-expressing parasites generated larger swellings in comparison with wild-type (L. major) while mice immunized with rEGFP and challenged with wild-type parasite were quite comparable in footpad swelling with control group without significant difference. However, both conventional and molecular approaches revealed no significant difference in parasite load between different groups. More importantly, no significant inflammatory responses were detected in groups with higher swelling size measured by interferon-γ (IFN-γ), interleukin (IL)-10, IL-5, and nitric oxide against frozen and thawed lysate of parasite as stimulator. Altogether, these results clearly revealed that EGFP protein expressed in prokaryotic and eukaryotic hosts is not an immunological reactive molecule and acts as a neutral protein without any side effects in mice. So, EGFP expressing Leishmania could be a safe and reliable substitution for wildtypes that simplifies in situ follow-up and eliminates the animal scarification wherever needed during the study