80 research outputs found
Accurate and linear time pose estimation from points and lines
The final publication is available at link.springer.comThe Perspective-n-Point (PnP) problem seeks to estimate the pose of a calibrated camera from n 3Dto-2D point correspondences. There are situations, though, where PnP solutions are prone to fail because feature point correspondences cannot be reliably estimated (e.g. scenes with repetitive patterns or with low texture). In such
scenarios, one can still exploit alternative geometric entities, such as lines, yielding the so-called Perspective-n-Line (PnL) algorithms. Unfortunately, existing PnL solutions are not as accurate and efficient as their point-based
counterparts. In this paper we propose a novel approach to introduce 3D-to-2D line correspondences into a PnP formulation, allowing to simultaneously process points and lines. For this purpose we introduce an algebraic line error
that can be formulated as linear constraints on the line endpoints, even when these are not directly observable. These constraints can then be naturally integrated within the linear formulations of two state-of-the-art point-based algorithms,
the OPnP and the EPnP, allowing them to indistinctly handle points, lines, or a combination of them. Exhaustive experiments show that the proposed formulation brings remarkable boost in performance compared to only point or
only line based solutions, with a negligible computational overhead compared to the original OPnP and EPnP.Peer ReviewedPostprint (author's final draft
Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences
We propose a fully automatic method for fitting a 3D morphable model to
single face images in arbitrary pose and lighting. Our approach relies on
geometric features (edges and landmarks) and, inspired by the iterated closest
point algorithm, is based on computing hard correspondences between model
vertices and edge pixels. We demonstrate that this is superior to previous work
that uses soft correspondences to form an edge-derived cost surface that is
minimised by nonlinear optimisation.Comment: To appear in ACCV 2016 Workshop on Facial Informatic
Towards Real-Time Head Pose Estimation: Exploring Parameter-Reduced Residual Networks on In-the-wild Datasets
Head poses are a key component of human bodily communication and thus a
decisive element of human-computer interaction. Real-time head pose estimation
is crucial in the context of human-robot interaction or driver assistance
systems. The most promising approaches for head pose estimation are based on
Convolutional Neural Networks (CNNs). However, CNN models are often too complex
to achieve real-time performance. To face this challenge, we explore a popular
subgroup of CNNs, the Residual Networks (ResNets) and modify them in order to
reduce their number of parameters. The ResNets are modifed for different image
sizes including low-resolution images and combined with a varying number of
layers. They are trained on in-the-wild datasets to ensure real-world
applicability. As a result, we demonstrate that the performance of the ResNets
can be maintained while reducing the number of parameters. The modified ResNets
achieve state-of-the-art accuracy and provide fast inference for real-time
applicability.Comment: 32nd International Conference on Industrial, Engineering & Other
Applications of Applied Intelligent Systems (IEA/AIE 2019
Towards key-frame extraction methods for 3D video: a review
The increasing rate of creation and use of 3D video content leads to a pressing need for methods capable of lowering
the cost of 3D video searching, browsing and indexing operations, with improved content selection performance.
Video summarisation methods specifically tailored for 3D video content fulfil these requirements. This paper presents
a review of the state-of-the-art of a crucial component of 3D video summarisation algorithms: the key-frame
extraction methods. The methods reviewed cover 3D video key-frame extraction as well as shot boundary detection
methods specific for use in 3D video. The performance metrics used to evaluate the key-frame extraction methods
and the summaries derived from those key-frames are presented and discussed. The applications of these methods
are also presented and discussed, followed by an exposition about current research challenges on 3D video
summarisation methods
Development of an In Vitro Model for the Multi-Parametric Quantification of the Cellular Interactions between Candida Yeasts and Phagocytes
We developed a new in vitro model for a multi-parameter characterization of the time course interaction of Candida fungal cells with J774 murine macrophages and human neutrophils, based on the use of combined microscopy, fluorometry, flow cytometry and viability assays. Using fluorochromes specific to phagocytes and yeasts, we could accurately quantify various parameters simultaneously in a single infection experiment: at the individual cell level, we measured the association of phagocytes to fungal cells and phagocyte survival, and monitored in parallel the overall phagocytosis process by measuring the part of ingested fungal cells among the total fungal biomass that changed over time. Candida albicans, C. glabrata, and C. lusitaniae were used as a proof of concept: they exhibited species-specific differences in their association rate with phagocytes. The fungal biomass uptaken by the phagocytes differed significantly according to the Candida species. The measure of the survival of fungal and immune cells during the interaction showed that C. albicans was the more aggressive yeast in vitro, destroying the vast majority of the phagocytes within five hours. All three species of Candida were able to survive and to escape macrophage phagocytosis either by the intraphagocytic yeast-to-hyphae transition (C. albicans) and the fungal cell multiplication until phagocytes burst (C. glabrata, C. lusitaniae), or by the avoidance of phagocytosis (C. lusitaniae). We demonstrated that our model was sensitive enough to quantify small variations of the parameters of the interaction. The method has been conceived to be amenable to the high-throughput screening of mutants in order to unravel the molecular mechanisms involved in the interaction between yeasts and host phagocytes
Identification of the CRE-1 Cellulolytic Regulon in Neurospora crassa
Background: In filamentous ascomycete fungi, the utilization of alternate carbon sources is influenced by the zinc finger transcription factor CreA/CRE-1, which encodes a carbon catabolite repressor protein homologous to Mig1 from Saccharomyces cerevisiae. In Neurospora crassa, deletion of cre-1 results in increased secretion of amylase and b-galactosidase. Methodology/Principal Findings: Here we show that a strain carrying a deletion of cre-1 has increased cellulolytic activity and increased expression of cellulolytic genes during growth on crystalline cellulose (Avicel). Constitutive expression of cre-1 complements the phenotype of a N. crassa Dcre-1 strain grown on Avicel, and also results in stronger repression of cellulolytic protein secretion and enzyme activity. We determined the CRE-1 regulon by investigating the secretome and transcriptome of a Dcre-1 strain as compared to wild type when grown on Avicel versus minimal medium. Chromatin immunoprecipitation-PCR of putative target genes showed that CRE-1 binds to only some adjacent 59-SYGGRG-39 motifs, consistent with previous findings in other fungi, and suggests that unidentified additional regulatory factors affect CRE-1 binding to promoter regions. Characterization of 30 mutants containing deletions in genes whose expression level increased in a Dcre-1 strain under cellulolytic conditions identified novel genes that affect cellulase activity and protein secretion
De novo Assembly of a 40 Mb Eukaryotic Genome from Short Sequence Reads: Sordaria macrospora, a Model Organism for Fungal Morphogenesis
Filamentous fungi are of great importance in ecology, agriculture, medicine, and biotechnology. Thus, it is not surprising that genomes for more than 100 filamentous fungi have been sequenced, most of them by Sanger sequencing. While next-generation sequencing techniques have revolutionized genome resequencing, e.g. for strain comparisons, genetic mapping, or transcriptome and ChIP analyses, de novo assembly of eukaryotic genomes still presents significant hurdles, because of their large size and stretches of repetitive sequences. Filamentous fungi contain few repetitive regions in their 30–90 Mb genomes and thus are suitable candidates to test de novo genome assembly from short sequence reads. Here, we present a high-quality draft sequence of the Sordaria macrospora genome that was obtained by a combination of Illumina/Solexa and Roche/454 sequencing. Paired-end Solexa sequencing of genomic DNA to 85-fold coverage and an additional 10-fold coverage by single-end 454 sequencing resulted in ∼4 Gb of DNA sequence. Reads were assembled to a 40 Mb draft version (N50 of 117 kb) with the Velvet assembler. Comparative analysis with Neurospora genomes increased the N50 to 498 kb. The S. macrospora genome contains even fewer repeat regions than its closest sequenced relative, Neurospora crassa. Comparison with genomes of other fungi showed that S. macrospora, a model organism for morphogenesis and meiosis, harbors duplications of several genes involved in self/nonself-recognition. Furthermore, S. macrospora contains more polyketide biosynthesis genes than N. crassa. Phylogenetic analyses suggest that some of these genes may have been acquired by horizontal gene transfer from a distantly related ascomycete group. Our study shows that, for typical filamentous fungi, de novo assembly of genomes from short sequence reads alone is feasible, that a mixture of Solexa and 454 sequencing substantially improves the assembly, and that the resulting data can be used for comparative studies to address basic questions of fungal biology
- …