Automatic 3D facial model and texture reconstruction from range scans

This paper presents a fully automatic approach to fitting a generic facial model to detailed range scans of human faces to reconstruct 3D facial models and textures with no manual intervention (such as specifying landmarks). A Scaling Iterative Closest Points (SICP) algorithm is introduced to compute the optimal rigid registrations between the generic model and the range scans with different sizes. And then a new template-fitting method, formulated in an optmization framework of minimizing the physically based elastic energy derived from thin shells, faithfully reconstructs the surfaces and the textures from the range scans and yields dense point correspondences across the reconstructed facial models. Finally, we demonstrate a facial expression transfer method to clone facial expressions from the generic model onto the reconstructed facial models by using the deformation transfer technique

Video face replacement

We present a method for replacing facial performances in video. Our approach accounts for differences in identity, visual appearance, speech, and timing between source and target videos. Unlike prior work, it does not require substantial manual operation or complex acquisition hardware, only single-camera video. We use a 3D multilinear model to track the facial performance in both videos. Using the corresponding 3D geometry, we warp the source to the target face and retime the source to match the target performance. We then compute an optimal seam through the video volume that maintains temporal consistency in the final composite. We showcase the use of our method on a variety of examples and present the result of a user study that suggests our results are difficult to distinguish from real video footage.National Science Foundation (U.S.) (Grant PHY-0835713)National Science Foundation (U.S.) (Grant DMS-0739255

Endophyte Microbiome Diversity in Micropropagated Atriplex canescens and Atriplex torreyi var griffithsii

Microbial diversity associated with micropropagated Atriplex species was assessed using microscopy, isolate culturing, and sequencing. Light, electron, and confocal microscopy revealed microbial cells in aseptically regenerated leaves and roots. Clone libraries and tag-encoded FLX amplicon pyrosequencing (TEFAP) analysis amplified sequences from callus homologous to diverse fungal and bacterial taxa. Culturing isolated some seed borne endophyte taxa which could be readily propagated apart from the host. Microbial cells were observed within biofilm-like residues associated with plant cell surfaces and intercellular spaces. Various universal primers amplified both plant and microbial sequences, with different primers revealing different patterns of fungal diversity. Bacterial and fungal TEFAP followed by alignment with sequences from curated databases revealed 7 bacterial and 17 ascomycete taxa in A. canescens, and 5 bacterial taxa in A. torreyi. Additional diversity was observed among isolates and clone libraries. Micropropagated Atriplex retains a complex, intimately associated microbiome which includes diverse strains well poised to interact in manners that influence host physiology. Microbiome analysis was facilitated by high throughput sequencing methods, but primer biases continue to limit recovery of diverse sequences from even moderately complex communities

Berry Flesh and Skin Ripening Features in Vitis vinifera as Assessed by Transcriptional Profiling

Background Ripening of fleshy fruit is a complex developmental process involving the differentiation of tissues with separate functions. During grapevine berry ripening important processes contributing to table and wine grape quality take place, some of them flesh- or skin-specific. In this study, transcriptional profiles throughout flesh and skin ripening were followed during two different seasons in a table grape cultivar ‘Muscat Hamburg’ to determine tissue-specific as well as common developmental programs. Methodology/Principal Findings Using an updated GrapeGen Affymetrix GeneChip® annotation based on grapevine 12×v1 gene predictions, 2188 differentially accumulated transcripts between flesh and skin and 2839 transcripts differentially accumulated throughout ripening in the same manner in both tissues were identified. Transcriptional profiles were dominated by changes at the beginning of veraison which affect both pericarp tissues, although frequently delayed or with lower intensity in the skin than in the flesh. Functional enrichment analysis identified the decay on biosynthetic processes, photosynthesis and transport as a major part of the program delayed in the skin. In addition, a higher number of functional categories, including several related to macromolecule transport and phenylpropanoid and lipid biosynthesis, were over-represented in transcripts accumulated to higher levels in the skin. Functional enrichment also indicated auxin, gibberellins and bHLH transcription factors to take part in the regulation of pre-veraison processes in the pericarp, whereas WRKY and C2H2 family transcription factors seems to more specifically participate in the regulation of skin and flesh ripening, respectively. Conclusions/Significance A transcriptomic analysis indicates that a large part of the ripening program is shared by both pericarp tissues despite some components are delayed in the skin. In addition, important tissue differences are present from early stages prior to the ripening onset including tissue-specific regulators. Altogether, these findings provide key elements to understand berry ripening and its differential regulation in flesh and skin.This study was financially supported by GrapeGen Project funded by Genoma España within a collaborative agreement with Genome Canada. The authors also thank The Ministerio de Ciencia e Innovacion for project BIO2008-03892 and a bilateral collaborative grant with Argentina (AR2009-0021). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewe

Building highly realistic facial modeling and animation: a survey

This paper provides a comprehensive survey on the techniques for human facial modeling and animation. The survey is carried out from two different perspectives: facial modeling, which concerns how to produce 3D face models, and facial animation, which regards how to synthesize dynamic facial expressions. To generate an individual face model, we can either perform individualization of a generic model or combine face models from an existing face collection. With respect to facial animation, we have further categorized the techniques into simulation-based, performance-driven and shape blend-based approaches. The strength and weakness of these techniques within each category are discussed, alongside with the applications of these techniques to various exploitations. In addition, a brief historical review of the technique evolution is provided. Limitations and future trend are discussed. Conclusions are drawn at the end of the paper