scholarly journals WATCHING GRASS GROW- A PILOT STUDY ON THE SUITABILITY OF PHOTOGRAMMETRIC TECHNIQUES FOR QUANTIFYING CHANGE IN ABOVEGROUND BIOMASS IN GRASSLAND EXPERIMENTS

2018 ◽  
Vol XLII-2 ◽  
pp. 539-542 ◽  
Author(s):  
M. Kröhnert ◽  
R. Anderson ◽  
J. Bumberger ◽  
P. Dietrich ◽  
W. S. Harpole ◽  
...  
Keyword(s):  
Pilot Study ◽  
Aboveground Biomass ◽  
Point Cloud ◽  
Cost Effective ◽  
Light Sheet ◽  
Projection System ◽  
Grassland Ecology ◽  
Dense Matching ◽  
3D Camera ◽  
Biomass Determination

Grassland ecology experiments in remote locations requiring quantitative analysis of the biomass in defined plots are becoming increasingly widespread, but are still limited by manual sampling methodologies. To provide a cost-effective automated solution for biomass determination, several photogrammetric techniques are examined to generate 3D point cloud representations of plots as a basis, to estimate aboveground biomass on grassland plots, which is a key ecosystem variable used in many experiments. Methods investigated include Structure from Motion (SfM) techniques for camera pose estimation with posterior dense matching as well as the usage of a Time of Flight (TOF) 3D camera, a laser light sheet triangulation system and a coded light projection system. In this context, plants of small scales (herbage) and medium scales are observed. In the first pilot study presented here, the best results are obtained by applying dense matching after SfM, ideal for integration into distributed experiment networks.

scholarly journals Semantic 3D Mapping from Deep Image Segmentation

2021 ◽  
Vol 11 (4) ◽  
pp. 1953
Author(s):  
Francisco Martín ◽  
Fernando González ◽  
José Miguel Guerrero ◽  
Manuel Fernández ◽  
Jonatan Ginés
Keyword(s):  
Point Cloud ◽  
Autonomous Mobile Robots ◽  
Semantic Mapping ◽  
Indoor Environments ◽  
3D Mapping ◽  
Direct Mapping ◽  
Learning Techniques ◽  
3D Camera ◽  
Deep Image ◽  
Boundary Pixel

The perception and identification of visual stimuli from the environment is a fundamental capacity of autonomous mobile robots. Current deep learning techniques make it possible to identify and segment objects of interest in an image. This paper presents a novel algorithm to segment the object’s space from a deep segmentation of an image taken by a 3D camera. The proposed approach solves the boundary pixel problem that appears when a direct mapping from segmented pixels to their correspondence in the point cloud is used. We validate our approach by comparing baseline approaches using real images taken by a 3D camera, showing that our method outperforms their results in terms of accuracy and reliability. As an application of the proposed algorithm, we present a semantic mapping approach for a mobile robot’s indoor environments.

Single Part of Building Extraction from Dense Matching Point Cloud

2018 ◽  
Vol 45 (7) ◽  
pp. 0710004
Author(s):  
闫利 Yan Li ◽  
魏峰 Wei Feng
Keyword(s):  
Point Cloud ◽  
Building Extraction ◽  
Dense Matching ◽  
Single Part

Developing a reliable and cost-effective follow-up programme after a short-term head and neck reconstructive mission in Ethiopia: a pilot study

2020 ◽  
Vol 58 (10) ◽  
pp. e175
Author(s):  
Daniel Bradley ◽  
Calum Honeyman ◽  
Vinod Patel ◽  
Julian Zeolla ◽  
Lucy Lester ◽  
...  
Keyword(s):  
Pilot Study ◽  
Head And Neck ◽  
Cost Effective ◽  
Short Term

scholarly journals Matrix therapy is a cost-effective solution to reduce amputation risk and improve quality of life: pilot and case studies

2019 ◽  
Vol 7 ◽  
pp. 2
Author(s):  
Pascal Desgranges ◽  
Taina Louissaint ◽  
Bertrand Godeau ◽  
Denis Barritault
Keyword(s):  
Quality Of Life ◽  
Pilot Study ◽  
Lower Extremity ◽  
Therapeutic Option ◽  
Stage Iv ◽  
Cost Effective ◽  
Healthcare Systems ◽  
Complete Healing ◽  
Effective Solution

Introduction: Chronic, non-healing ulcers remain one of the most challenging clinical situations for health care practitioners. Often, conventional treatments fail and lead to amputation, further decreasing the patient's quality of life and resulting in enormous medical expenditures for healthcare systems. Here we evaluated the use of and cost-effectiveness of the RGTA (ReGeneraTing Agents) medical device CACIPLIQ20 (OTR4120) for chronic lower-extremity ulcers in patients with Leriche and Fontaine Stage IV peripheral arterial disease who were not eligible for revascularization. Methods: This uncontrolled pilot study included 14 chronic lower extremity ulcers in 12 patients in one hospital. The pilot study included 12 patients with TcPO2 < 20 mm Hg and ABPI < 0.5 who had either a minimum of one chronic lower extremity ulcer or a chronic ulcer related to amputation. OTR4120 was applied twice a week or until complete healing, for up to 12 weeks. Ulcer surface area reduction (%)after 2, 4, 8 and 12 weeks, appearance after 4 weeks, and healing after 12 weeks were measured and recorded. Results: A 35% reduction in ulcer size was achieved after 4 weeks. 7 (50%) out of 14 ulcers completely healed within 1 to 3 months of treatment. Discussion: OTR4120 is an effective therapeutic option for patients with chronic lower extremity ulcers, can provide major improvement of quality of life and has the added benefit of being a significant cost-effective solution for healthcare systems.

scholarly journals Jugular Bulb Oximetry for Prediction of Vasospasm Following Subarachnoid Hemorrhage

2004 ◽  
Vol 31 (1) ◽  
pp. 80-86 ◽  
Author(s):  
Navraj S. Heran ◽  
Stephen J. Hentschel ◽  
Brian D. Toyota
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Pilot Study ◽  
Observational Study ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Cost Effective ◽  
Jugular Bulb ◽  
Significant Rise ◽  
Cerebral Oxygen ◽  
Blood Samples ◽  
Jugular Bulb Catheter

Background:Cerebral vasospasm adversely impacts the outcome of those suffering aneurysmal subarachnoid hemorrhage (SAH). Prediction of vasospasm could improve outcomes. We hypothesized that preclinical vasospasm would be heralded by an increase in cerebral oxygen extractions (AVDO2) which could be detected by jugular bulb oximetry. A pilot study was conducted to address this hypothesis.Methods:Fourteen consenting patients with aneurysmal SAH, undergoing early surgery, were entered into the study. Four patients were withdrawn from the study secondary to failure of catheters or religious belief. At the time of craniotomy, a jugular bulb catheter was placed. Post-operatively, arterial and jugular bulb blood samples were taken every 12 hours to calculate AVDO2. As this was an observational study, no change in management occurred based on measurements.Results:Four of 10 patients had clinical vasospasm. These patients had a significant rise in AVDO2 approximately one day prior to the onset of neurologic deficits (P<0.001). Symptoms resolved along with a significant improvement in AVDO2 on instituting hypertensive, hemo-dilutional, and hypervolemic therapy in these patients. The six patients who did not exhibit clinical vasospasm did not demonstrate significant rise in AVDO2.Conclusion:Jugular bulb oximetry is simple and cost effective. Increases in AVDO2 using this technique were predictive of clinically evident vasospasm in the subsequent hours to days. This investigation supports a larger study to assess the utility of jugular bulb oximetry in predicting vasospasm in aneurysmal SAH.

scholarly journals UAV-BASED POINT CLOUD GENERATION FOR OPEN-PIT MINE MODELLING

2015 ◽  
Vol XL-1/W4 ◽  
pp. 313-320 ◽  
Author(s):  
M. Shahbazi ◽  
G. Sohn ◽  
J. Théau ◽  
P. Ménard
Keyword(s):  
System Integration ◽  
Point Cloud ◽  
Three Dimensional ◽  
3D Modelling ◽  
Bundle Adjustment ◽  
Aerial Imagery ◽  
Open Pit ◽  
Sensor Calibration ◽  
Dense Matching ◽  
Mapping Techniques

Along with the advancement of unmanned aerial vehicles (UAVs), improvement of high-resolution cameras and development of vision-based mapping techniques, unmanned aerial imagery has become a matter of remarkable interest among researchers and industries. These images have the potential to provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modelling. In this paper, we present our theoretical and technical experiments regarding the development, implementation and evaluation of a UAV-based photogrammetric system for precise 3D modelling. This system was preliminarily evaluated for the application of gravel-pit surveying. The hardware of the system includes an electric powered helicopter, a 16-megapixels visible camera and inertial navigation system. The software of the system consists of the in-house programs built for sensor calibration, platform calibration, system integration and flight planning. It also includes the algorithms developed for structure from motion (SfM) computation including sparse matching, motion estimation, bundle adjustment and dense matching.

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