Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments

2014 ◽  
Vol 36 (7) ◽  
pp. 1325-1339 ◽  
Author(s):  
Catalin Ionescu ◽  
Dragos Papava ◽  
Vlad Olaru ◽  
Cristian Sminchisescu
Keyword(s):  
Large Scale ◽  
Natural Environments ◽  
Predictive Methods ◽  
Human Sensing

scholarly journals ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition

2021 ◽  
Author(s):  
Anil S. Baslamisli ◽  
Partha Das ◽  
Hoang-An Le ◽  
Sezer Karaoglu ◽  
Theo Gevers
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
State Of The Art ◽  
Image Decomposition ◽  
Natural Environments ◽  
Decomposition Algorithms ◽  
Ambient Light ◽  
Fine Grained ◽  
Large Scale Dataset ◽  
Direct Illumination

AbstractIn general, intrinsic image decomposition algorithms interpret shading as one unified component including all photometric effects. As shading transitions are generally smoother than reflectance (albedo) changes, these methods may fail in distinguishing strong photometric effects from reflectance variations. Therefore, in this paper, we propose to decompose the shading component into direct (illumination) and indirect shading (ambient light and shadows) subcomponents. The aim is to distinguish strong photometric effects from reflectance variations. An end-to-end deep convolutional neural network (ShadingNet) is proposed that operates in a fine-to-coarse manner with a specialized fusion and refinement unit exploiting the fine-grained shading model. It is designed to learn specific reflectance cues separated from specific photometric effects to analyze the disentanglement capability. A large-scale dataset of scene-level synthetic images of outdoor natural environments is provided with fine-grained intrinsic image ground-truths. Large scale experiments show that our approach using fine-grained shading decompositions outperforms state-of-the-art algorithms utilizing unified shading on NED, MPI Sintel, GTA V, IIW, MIT Intrinsic Images, 3DRMS and SRD datasets.

Development and Testing of an Unmanned Aerial Vehicle for Large Scale Particle Image Velocimetry

2014 ◽  
Author(s):  
Christopher Pagano ◽  
Flavia Tauro ◽  
Salvatore Grimaldi ◽  
Maurizio Porfiri
Keyword(s):  
Particle Image Velocimetry ◽  
Large Scale ◽  
Field Experiments ◽  
Particle Image ◽  
Low Cost ◽  
Surface Flow ◽  
Natural Environments ◽  
Natural Stream ◽  
Image Velocimetry ◽  
Scale Particle

Large scale particle image velocimetry (LSPIV) is a nonintrusive environmental monitoring methodology that allows for continuous characterization of surface flows in natural catchments. Despite its promise, the implementation of LSPIV in natural environments is limited to areas accessible to human operators. In this work, we propose a novel experimental configuration that allows for unsupervised LSPIV over large water bodies. Specifically, we design, develop, and characterize a lightweight, low cost, and stable quadricopter hosting a digital acquisition system. An active gimbal maintains the camera lens orthogonal to the water surface, thus preventing severe image distortions. Field experiments are performed to characterize the vehicle and assess the feasibility of the approach. We demonstrate that the quadricopter can hover above an area of 1×1m2 for 4–5 minutes with a payload of 500g. Further, LSPIV measurements on a natural stream confirm that the methodology can be reliably used for surface flow studies.

scholarly journals In which natural environments are people happiest? Large-scale experience sampling in the Netherlands

2021 ◽  
Vol 205 ◽  
pp. 103972
Author(s):  
Sjerp de Vries ◽  
Wim Nieuwenhuizen ◽  
Hans Farjon ◽  
Arjen van Hinsberg ◽  
Joep Dirkx
Keyword(s):  
The Netherlands ◽  
Large Scale ◽  
Experience Sampling ◽  
Natural Environments

Balancing Environmental Remediation, Environmental Justice, and Health Disparities: the Case of Lake Apopka, Florida

2019 ◽  
Vol 3 (1) ◽  
pp. 1-7
Author(s):  
Anne Saville ◽  
Alison Adams
Keyword(s):  
Water Quality ◽  
Environmental Remediation ◽  
Large Scale ◽  
The United States ◽  
Government Agencies ◽  
Natural Environments ◽  
Conventional Agriculture ◽  
Non Profit ◽  
Lake Apopka ◽  
Non Profit Organizations

Agricultural production in the United States provides numerous economic contributions from the national scale to the local, providing farmworker and laborer jobs for hundreds of thousands of people [1]. Unfortunately, conventional agricultural operations are often associated with pesticides, herbicides, and fertilizers, which can cause environmental degradation and health problems. Large-scale conventional agriculture is often using pesticide, herbicide, and fertilizer intensive, and these chemicals may contaminate natural environments, harming wildlife, and degrading water quality. When contamination incidents occur, government agencies and non-profit organizations respond in various ways, including environmental remediation. These efforts can be successful in restoring water quality and improving biodiversity. But, what happens when clean-up efforts are able to improve the physical environment but do not address human health? We use the case of Lake Apopka, Florida, to analyze a case of agricultural contamination that resulted in damage to the environment and the health of the farmworkers who were exposed to these harmful chemicals. Our analysis explores how government agencies and non-profit organizations were successful in their conservation efforts, but failed to help the farmworkers and other people who were sick as a result of exposure to toxic chemicals. We conclude with recommendations for policy makers and environmentalists to better address and include marginalized or vulnerable communities in environmental remediation projects.

scholarly journals Residential green space in childhood is associated with lower risk of psychiatric disorders from adolescence into adulthood

2019 ◽  
Vol 116 (11) ◽  
pp. 5188-5193 ◽  
Author(s):  
Kristine Engemann ◽  
Carsten Bøcker Pedersen ◽  
Lars Arge ◽  
Constantinos Tsirogiannis ◽  
Preben Bo Mortensen ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Psychiatric Disorders ◽  
Lower Risk ◽  
Large Scale ◽  
Vegetation Index ◽  
Green Space ◽  
Wide Spectrum ◽  
Natural Environments ◽  
Parental History

Urban residence is associated with a higher risk of some psychiatric disorders, but the underlying drivers remain unknown. There is increasing evidence that the level of exposure to natural environments impacts mental health, but few large-scale epidemiological studies have assessed the general existence and importance of such associations. Here, we investigate the prospective association between green space and mental health in the Danish population. Green space presence was assessed at the individual level using high-resolution satellite data to calculate the normalized difference vegetation index within a 210 × 210 m square around each person’s place of residence (∼1 million people) from birth to the age of 10. We show that high levels of green space presence during childhood are associated with lower risk of a wide spectrum of psychiatric disorders later in life. Risk for subsequent mental illness for those who lived with the lowest level of green space during childhood was up to 55% higher across various disorders compared with those who lived with the highest level of green space. The association remained even after adjusting for urbanization, socioeconomic factors, parental history of mental illness, and parental age. Stronger association of cumulative green space presence during childhood compared with single-year green space presence suggests that presence throughout childhood is important. Our results show that green space during childhood is associated with better mental health, supporting efforts to better integrate natural environments into urban planning and childhood life.

scholarly journals Improving herpetological surveys in eastern North America using the environmental DNA method

Genome ◽  
2016 ◽  
Vol 59 (11) ◽  
pp. 991-1007 ◽  
Author(s):  
Anaïs Lacoursière-Roussel ◽  
Yohann Dubois ◽  
Eric Normandeau ◽  
Louis Bernatchez
Keyword(s):  
Large Scale ◽  
Habitat Type ◽  
Environmental Dna ◽  
Conservation Strategies ◽  
Natural Environments ◽  
Detection Rates ◽  
Survey Tool ◽  
Declining Species ◽  
Species Specific ◽  
Wood Turtle

Among vertebrates, herpetofauna has the highest proportion of declining species. Detection of environmental DNA (eDNA) is a promising method towards significantly increasing large-scale herpetological conservation efforts. However, the integration of eDNA results within a management framework requires an evaluation of the efficiency of the method in large natural environments and the calibration of eDNA surveys with the quantitative monitoring tools currently used by conservation biologists. Towards this end, we first developed species-specific primers to detect the wood turtle (Glyptemys insculpta) a species at risk in Canada, by quantitative PCR (qPCR). The rate of eDNA detection obtained by qPCR was also compared to the relative abundance of this species in nine rivers obtained by standardized visual surveys in the Province of Québec (Canada). Second, we developed multi-species primers to detect North American amphibian and reptile species using eDNA metabarcoding analysis. An occurrence index based on the distribution range and habitat type was compared with the eDNA metabarcoding dataset from samples collected in seven lakes and five rivers. Our results empirically support the effectiveness of eDNA metabarcoding to characterize herpetological species distributions. Moreover, detection rates provided similar results to standardized visual surveys currently used to develop conservation strategies for the wood turtle. We conclude that eDNA detection rates may provide an effective semiquantitative survey tool, provided that assay calibration and standardization is performed.

A Theoretical Model of Wayfinding in Virtual Environments: Proposed Strategies for Navigational Aiding

1999 ◽  
Vol 8 (6) ◽  
pp. 671-685 ◽  
Author(s):  
Jui Lin Chen ◽  
Kay M. Stanney
Keyword(s):  
Theoretical Model ◽  
Virtual Environments ◽  
Virtual Environment ◽  
Large Scale ◽  
Cognitive Mapping ◽  
Spatial Information ◽  
Current Model ◽  
Spatial Knowledge ◽  
Natural Environments ◽  
Virtual Spaces

This paper proposes a theoretical model of wayfinding that can be used to guide the design of navigational aiding in virtual environments. Based on an evaluation of wayfinding studies in natural environments, this model divides the wayfinding process into three main subprocesses: cognitive mapping, wayfinding plan development, and physical movement or navigation through an environment. While this general subdivision has been proposed before, the current model further delineates the wayfinding process, including the distinct influences of spatial information, spatial orientation, and spatial knowledge. The influences of experience, abilities, search strategies, motivation, and environmental layout on the wayfinding process are also considered. With this specification of the wayfinding process, a taxonomy of navigational tools is then proposed that can be used to systematically aid the specified wayfinding subprocesses. If effectively applied to the design of a virtual environment, the use of such tools should lead to reduced disorientation and enhanced wayfinding in large-scale virtual spaces. It is also suggested that, in some cases, this enhanced wayfinding performance may be at the expense of the acquisition of an accurate cognitive map of the virtual environment being traversed.

scholarly journals Pan-Eurasian Experiment (PEEX): towards a holistic understanding of the feedbacks and interactions in the land–atmosphere–ocean–society continuum in the northern Eurasian region

2016 ◽  
Vol 16 (22) ◽  
pp. 14421-14461 ◽  
Author(s):  
Hanna K. Lappalainen ◽  
Veli-Matti Kerminen ◽  
Tuukka Petäjä ◽  
Theo Kurten ◽  
Aleksander Baklanov ◽  
...  
Keyword(s):  
Research Agenda ◽  
Large Scale ◽  
System Analysis ◽  
Global Climate ◽  
The Arctic ◽  
Research Approach ◽  
Natural Environments ◽  
System Perspective ◽  
Holistic Understanding ◽  
Eurasian Region

Abstract. The northern Eurasian regions and Arctic Ocean will very likely undergo substantial changes during the next decades. The Arctic–boreal natural environments play a crucial role in the global climate via albedo change, carbon sources and sinks as well as atmospheric aerosol production from biogenic volatile organic compounds. Furthermore, it is expected that global trade activities, demographic movement, and use of natural resources will be increasing in the Arctic regions. There is a need for a novel research approach, which not only identifies and tackles the relevant multi-disciplinary research questions, but also is able to make a holistic system analysis of the expected feedbacks. In this paper, we introduce the research agenda of the Pan-Eurasian Experiment (PEEX), a multi-scale, multi-disciplinary and international program started in 2012 (https://www.atm.helsinki.fi/peex/). PEEX sets a research approach by which large-scale research topics are investigated from a system perspective and which aims to fill the key gaps in our understanding of the feedbacks and interactions between the land–atmosphere–aquatic–society continuum in the northern Eurasian region. We introduce here the state of the art for the key topics in the PEEX research agenda and present the future prospects of the research, which we see relevant in this context.

scholarly journals Enhancement of Phosphate Absorption by Garden Plants by Genetic Engineering: A New Tool for Phytoremediation

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Keisuke Matsui ◽  
Junichi Togami ◽  
John G. Mason ◽  
Stephen F. Chandler ◽  
Yoshikazu Tanaka
Keyword(s):  
Transgenic Plants ◽  
Water Hyacinth ◽  
Inorganic Phosphate ◽  
Large Scale ◽  
Environmental Water ◽  
Natural Environments ◽  
Essential Factor ◽  
Starvation Response ◽  
Pi Starvation ◽  
Garden Plants

Although phosphorus is an essential factor for proper plant growth in natural environments, an excess of phosphate in water sources causes serious pollution. In this paper we describe transgenic plants which hyperaccumulate inorganic phosphate (Pi) and which may be used to reduce environmental water pollution by phytoremediation. AtPHR1, a transcription factor for a key regulator of the Pi starvation response inArabidopsis thaliana, was overexpressed in the ornamental garden plantsTorenia, Petunia, and Verbena.The transgenic plants showed hyperaccumulation of Pi in leaves and accelerated Pi absorption rates from hydroponic solutions. Large-scale hydroponic experiments indicated that the enhanced ability to absorb Pi in transgenic torenia (AtPHR1) was comparable to water hyacinth a plant that though is used for phytoremediation causes overgrowth problems.

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