Flowing ConvNets for Human Pose Estimation in Videos

The objective of this work is human pose estimation in videos, where multiple frames are available. We investigate a ConvNet architecture that is able to benefit from temporal context by combining information across the multiple frames using optical flow. To this end we propose a network architecture with the following novelties: (i) a deeper network than previously investigated for regressing heatmaps; (ii) spatial fusion layers that learn an implicit spatial model; (iii) optical flow is used to align heatmap predictions from neighbouring frames; and (iv) a final parametric pooling layer which learns to combine the aligned heatmaps into a pooled confidence map. We show that this architecture outperforms a number of others, including one that uses optical flow solely at the input layers, one that regresses joint coordinates directly, and one that predicts heatmaps without spatial fusion. The new architecture outperforms the state of the art by a large margin on three video pose estimation datasets, including the very challenging Poses in the Wild dataset, and outperforms other deep methods that don't use a graphical model on the single-image FLIC benchmark (and also Chen & Yuille and Tompson et al. in the high precision region).Comment: ICCV'1

Nutrition and Feeding Behavior of Goats and Sheep Grazing Deciduous Shrub-Woodland in Northeastern Brazil

Production of sheep and goats in the Brazilian Northeast is important for the livelihood of both subsistence and market-oriented producers. Seasonal nutritional stress oh animals in the caatinga vegetational zone of this region causes periodic high mortality and chronically low productivity. Under such conditions, the survivability of goats has been higher than for other domestic livestock. Possible reasons for this include unique aspects of dietary selection and goat feeding behavior. The objectives of this research were to seasonally determine the botanical and nutritive content of goat and sheep diets, to determine forage intake by grazing goats and sheep, and to compare their feeding behavior. Dietary selections by sheep and goats were similar during the dry season, but diverged markedly during the wet season. Leaf litter from the deciduous trees was the major dietary component for both species during the dry season, and provided the bulk of dry season forage. Current hypotheses predict that goats select diets of higher nutritional quality and have a greater forage intake than do sheep. Goats selected diets significantly (P.05) in cell wall content, and lower (P This study confirmed the vertical stratification of foraging by goats and sheep. Sheep foraged more in lower vertical strata than did goats. Goats spent about 4% of their grazing time in a bipedal stance, while sheep virtually never used a bipedal stance to feed. In addition, no nutritional advantage was found for goats over sheep through use of a bipedal stance. This latter finding is constrained by the deciduous nature of the caatinga woodland during the dry season

Guided Proofreading of Automatic Segmentations for Connectomics

Automatic cell image segmentation methods in connectomics produce merge and split errors, which require correction through proofreading. Previous research has identified the visual search for these errors as the bottleneck in interactive proofreading. To aid error correction, we develop two classifiers that automatically recommend candidate merges and splits to the user. These classifiers use a convolutional neural network (CNN) that has been trained with errors in automatic segmentations against expert-labeled ground truth. Our classifiers detect potentially-erroneous regions by considering a large context region around a segmentation boundary. Corrections can then be performed by a user with yes/no decisions, which reduces variation of information 7.5x faster than previous proofreading methods. We also present a fully-automatic mode that uses a probability threshold to make merge/split decisions. Extensive experiments using the automatic approach and comparing performance of novice and expert users demonstrate that our method performs favorably against state-of-the-art proofreading methods on different connectomics datasets.Comment: Supplemental material available at http://rhoana.org/guidedproofreading/supplemental.pd

A preliminary checklist of fungi at the Boston Harbor Islands

Between December 2012 and May 2017, we conducted a fungal inventory at the Boston Harbor Islands National Recreation Area (BHI) in Massachusetts. We extensively sampled 4 sites (Grape Island, Peddocks Island, Thompson Island, and World's End peninsula) and occasionally visited 4 others for sampling (Calf Island, Great Brewster Island, Slate Island, and Webb Memorial State Park). We made over 900 collections, of which 313 have been identified. The survey yielded 172 species in 123 genera, 62 families, 24 orders, 11 classes, and 2 phyla. We report 4 species as new, but not formally described, in the genera Orbilia, Resupinatus, and Xylaria. Another collection in the genus Lactarius may be new to science, but further morphological and molecular work is needed to confirm this conclusion. Additionally, Orbilia aprilis is a new report for North America, Proliferodiscus earoleucus represents only the second report for the US, and Chrysosporium sulfureum, a common fungus of some cheeses, was discovered on woodlice (Crustacea: Malacostraca: Isopoda: Oniscidea). We discuss our findings in the light of DNA-based identifications using the ITS ribosomal DNA region, including the advantages and disadvantages of this approach, and stress the need for biodiversity studies in urbanized areas during all seasons

Sareomycetes: more diverse than meets the eye

Since its resurrection, the resinicolous discomycete genus Sarea has been accepted as containing two species, one with black apothecia and pycnidia, and one with orange. We investigate this hypothesis using three ribosomal (nuITS, nuLSU, mtSSU) regions from and morphological examination of 70 specimens collected primarily in Europe and North America. The results of our analyses support separation of the traditional Sarea difformis s.lat. and Sarea resinae s.lat. into two distinct genera, Sarea and Zythia. Sarea as circumscribed is shown to conservatively comprise three phylospecies, with one corresponding to Sarea difformis s.str. and two, morphologically indistinguishable, corresponding to the newly combined Sarea coeloplata. Zythia is provisionally maintained as monotypic, containing only a genetically and morphologically variable Z. resinae. The new genus Atrozythia is erected for the new species A. klamathica. Arthrographis lignicola is placed in this genus on molecular grounds, expanding the concept of Sareomycetes by inclusion of a previously unknown type of asexual morph. Dating analyses using additional marker regions indicate the emergence of the Sareomycetes was roughly concurrent with the diversification of the genus Pinus, suggesting that this group of fungi emerged to exploit the newly-available resinous ecological niche supplied by Pinus or another, extinct group of conifers. Our phylogeographic studies also permitted us to study the introductions of these fungi to areas where they are not native, including Antarctica, Cape Verde, and New Zealand and are consistent with historical hypotheses of introduction

Livestock preference for endophyte-infected or endophyte-free Oxytropis sericea, Ipomoea carnea, and Ipomoea asarifolia

Fungal endophyte-infected forages have been shown to alter herbivore feeding preferences. The objective of this experiment was to compare the preference of cattle, sheep, and goats for plants containing (E+) and not containing (E-) fungal endophytes using freshly harvested Oxytropis sericea, Ipomoea carnea, and Ipomoea asarifolia. Goats and sheep rejected all forage choices regardless of endophyte status except for grass and alfalfa hay. Endophyte status had no influence on cattle forage preferences. Cattle rejected all Oxytropis sericea E+ and E- choices. Cattle discriminated between Ipomoea species, preferring Ipomoea carnea to Ipomoea asarifolia (P = 0.004). In all comparisons, Ipomoea carnea was selected over Ipomoea asarifolia. Cattle did not discriminate between E+ and E- plants of either species (P \u3e 0.33). Cattle preferred E+ Ipomoea carnea over E- Ipomoea asarifolia (P = 0.03), E- Ipomoea carnea over E- Ipomoea asarifolia (P = 0.003), E- Ipomoea carnea over E+ Ipomoea asarifolia (P = 0.001), and E+ Ipomoea carnea over E+ Ipomoea asarifolia (P = 0.01). Nutritional composition, including nonstructural carbohydrate concentrations, did not explain cattle preferences, as Ipomoea asarifolia contained higher total carbohydrate concentrations than did Ipomoea carnea. The presence of ergot and indole diterpene alkaloids in E+ Ipomoea asarifolia, or swainsonine in E+ Oxytropis sericea and E+ Ipomoea carnea did not influence cattle preference because cattle did not discriminate between E- and E+ plants. This study suggests that for these specific toxic plants, endophyte status plays no part in preferences of grazing cattle. For grazing animals, selection by livestock is related to forage scarcity or low nutrient content in the other available forage

Consistent Video Filtering for Camera Arrays

International audienceVisual formats have advanced beyond single-view images and videos: 3D movies are commonplace, researchers have developed multi-view navigation systems, and VR is helping to push light field cameras to mass market. However, editing tools for these media are still nascent, and even simple filtering operations like color correction or stylization are problematic: naively applying image filters per frame or per view rarely produces satisfying results due to time and space inconsistencies. Our method preserves and stabilizes filter effects while being agnostic to the inner working of the filter. It captures filter effects in the gradient domain, then uses \emph{input} frame gradients as a reference to impose temporal and spatial consistency. Our least-squares formulation adds minimal overhead compared to naive data processing. Further, when filter cost is high, we introduce a filter transfer strategy that reduces the number of per-frame filtering computations by an order of magnitude, with only a small reduction in visual quality. We demonstrate our algorithm on several camera array formats including stereo videos, light fields, and wide baselines

Studies of Two-Phase Flow at a Chute Aerator with Experiments and CFD Modelling

The chute aerator of a spillway is a structure in such a sense that air is, in the intense emulsification, entrained into the highvelocity water flow. Correctly predicting the air entrainment and two-phase flow pattern at the aerator would contribute to reliable spillway operation. Based on experimental data, 2D numerical simulations are preformed to predict streamwise air concentrations in the aerated flow, in which a two-fluid model is used. Depending on the air bubble size, relatively good agreement is seen with the experiments in the air cavity zone. The simulations give rise to higher air concentration downstream of the cavity, which is presumably due to underestimation of the interfacial forces in the two-fluid model

The Ecologic Impact of the Interactions Among Microorganisms and Aquatic Contaminants in Lake Erie Phase III Parts 5, 6, and 7

This study was supported in part by the Office of Water Resources Research. U.S. Department of the Interior, under Project B-025-OHIO(print) 172 p.Part 5: List of Figures -- List of Tables -- Introduction -- Literature Review -- Materials and Methods -- Results -- Discussion -- Summary -- BibliographyPart 6: List of Figures -- List of Tables -- Introduction -- Review of Literature -- Materials and Methods -- Results -- Discussion -- Appendix A -- Appendix B -- BibliographyPart 7: List of Illustrations -- List of Tables -- Introduction -- Review of Literature -- Materials and Methods -- Results -- Discussion -- Summary -- Literature Cite