A Colour based Approach for Face Segmentation from Video Images under Low Luminance Levels

2010 ◽  
Author(s):  
S. Anishenko ◽  
D. Shaposhnikov ◽  
R. Comley ◽  
X. Gao
Keyword(s):  
Video Images ◽  
Low Luminance ◽  
Face Segmentation

Computing cell tractions from particle displacements on silicone rubber substrata

1994 ◽  
Vol 52 ◽  
pp. 162-163
Author(s):  
Tim Oliver ◽  
Akira Ishihara ◽  
Ken Jacobsen ◽  
Micah Dembo
Keyword(s):  
Plane Stress ◽  
Linear Elasticity ◽  
Silicone Rubber ◽  
Mathematical Analysis ◽  
Elastic Recovery ◽  
Video Images ◽  
Cell Traction Forces ◽  
Latex Beads ◽  
Cell Traction ◽  
Better Than

In order to better understand the distribution of cell traction forces generated by rapidly locomoting cells, we have applied a mathematical analysis to our modified silicone rubber traction assay, based on the plane stress Green’s function of linear elasticity. To achieve this, we made crosslinked silicone rubber films into which we incorporated many more latex beads than previously possible (Figs. 1 and 6), using a modified airbrush. These films could be deformed by fish keratocytes, were virtually drift-free, and showed better than a 90% elastic recovery to micromanipulation (data not shown). Video images of cells locomoting on these films were recorded. From a pair of images representing the undisturbed and stressed states of the film, we recorded the cell’s outline and the associated displacements of bead centroids using Image-1 (Fig. 1). Next, using our own software, a mesh of quadrilaterals was plotted (Fig. 2) to represent the cell outline and to superimpose on the outline a traction density distribution. The net displacement of each bead in the film was calculated from centroid data and displayed with the mesh outline (Fig. 3).

Comparing estimated and actual visual acuity at high and low luminance

2006 ◽  
Author(s):  
Johnell O. Brooks ◽  
Richard A. Tyrrell ◽  
Benjamin R. Stephens
Keyword(s):  
Visual Acuity ◽  
Low Luminance

“Are You Religious or are You Saved?”

2012 ◽  
Vol 6 (1) ◽  
pp. 47-63
Author(s):  
Stephen Pihlaja
Keyword(s):  
Multimodal Approach ◽  
Membership Categorization Analysis ◽  
Evangelical Christian ◽  
Video Images ◽  
User Comments ◽  
Membership Categorization ◽  
Longitudinal Observation

Using membership categorization analysis, this article investigates membership categories in a YouTube video made by an Evangelical Christian in which he differentiates between “saved” and “religious” users. Analysis will take a discourse-centred, multimodal approach grounded in longitudinal observation, using analysis of video discourse to instruct analysis of video images and user comments. Findings will show that categorization is accomplished by using recognized categories with ambiguous descriptions of category-bound activities that include metaphors, such as “being hungry for God” and not “hanging out with atheists.” These categories are recognized by commenters on the video, but the category bound activities applied to the category members are disputed. Findings will also show that scriptural reference plays an important role in categorization in the video, drawing on direct Bible quotes as well as paraphrases of key passages.

Effects of Black Luminance Level on Image Quality

2019 ◽  
Vol 2019 (1) ◽  
pp. 104-107
Author(s):  
Ye Seul Baek ◽  
Youngshin Kwak ◽  
Sehyeok Park
Keyword(s):  
Image Quality ◽  
Luminance Level ◽  
Psychophysical Experiment ◽  
Image Histogram ◽  
Affect Image Quality ◽  
Low Luminance ◽  
Black Level ◽  
Oled Display ◽  
Dark Room

The image quality is affected by the black luminance level of the image. This research aimed to investigate how low luminance levels are required to maintain image quality. The psychophysical experiment was carried out in a dark room using OLED display. Total of 6 different black luminance levels (0.003, 0.05, 0.1, 0.2, 0.3, and 1 cd/m2) were used in the experiment. Total of 20 participants was invited to evaluate the image quality. For the experiment, twelve test images are used and these test images categorized into three groups as dark, medium bright and bright image group by image histogram distribution. Each image is rendered by adjusting six different black luminance levels. Result found that the black level is higher than 0.1 cd/m2, the preference for the image is decreased. The best performance is achieved when the black level is 0.003 cd/m2, but there is no big difference from 0.1 cd/m2. The final result shows that a change in black level between about 0.003 cd/m2 and 0.1 cd/m2 does not significantly affect image quality.

Relationship between Faithfulness and Preference of Stars in a Planetarium

2019 ◽  
Vol 2 (1) ◽  
pp. 10402-1-10402-11
Author(s):  
Midori Tanaka ◽  
Takahiko Horiuchi ◽  
Ken’ichi Otani
Keyword(s):  
Light Source ◽  
Preference Rating ◽  
Experimental Procedure ◽  
Male And Female ◽  
Astronomical Observations ◽  
Low Luminance ◽  
Projection Pattern ◽  
The Relationship ◽  
Star Field

Abstract A planetarium imitates a starry sky with physical and technical limitations using a dome, projector, and light source. It is widely used for entertainment, and astronomy and physics educations. In our previous study, we investigated the evaluation for faithful reproduction of a star field in a planetarium by performing psychometric experiments with 20 observers for plural projection patterns with different reproduction factors (color, luminance, and size of projected stars). In this study, we investigate the relationship between faithfulness and preference of a star field in a planetarium through a psychometric experiment with 47 observers. The experimental procedure followed the previous study. The rating of faithfulness improved for the projection pattern with a smaller star size. For the preference evaluation, the projection pattern with low luminance significantly lowered the preference rating. The results of the experiment indicate that the preferable star reproduction was different between male and female observers, whereas the faithful star reproduction was not significantly different in the evaluations between male and female observers. The male observers sought a faithful star reproduction as the preferred reproduction. In contrast, the female observers did not feel the faithful star reproduction preferable, and evaluated the more brilliant star reproduction as the preferred reproduction. These results were not dependent on the experience in astronomical observations.

STRUCTURAL AND LOGISTIC MODEL OF MATERIAL FLOWS ON DIGITALLIVESTOCK FARM

2020 ◽  
pp. 26-32
Author(s):  
VLADIMIR V KIRSANOV VLADIMIR V ◽  
Keyword(s):  
Functional Model ◽  
Base Stations ◽  
Farm Animals ◽  
Biological Objects ◽  
Livestock Breeding ◽  
Video Images ◽  
Genetic Potential ◽  
Common Control ◽  
Biotechnical System ◽  
Multi Agent

The problems of the digitalization of livestock enterprises are closely related to the construction of models and algorithms describing the functioning of individual technological processes and subsystems united by a common control system. Based on the cluster approach, three groups of tasks for the intellectualization and digitalization of objects in livestock breeding are formulated: 1) recognition of images of biological objects and models of their group and individual behavior, 2) genomic assessment of farm animals, prediction of their genetic potential, with the possibility of better adaptation to technologies and specifi c economic conditions, 3) multi-agent management of automated and robotic technical means. The authors initialized the video images of biological objects, developed a structural and functional model of a complex biotechnical system “Man-Machine-Animal”, including automated workstations of key specialists, signal receiving-and-transmitting base stations, technological modules for animal service (feeding, watering, milking, microclimate, etc.), representing local biotechnical systems. The paper presents a structural-and-logistic “funnel” model of a livestock farm functioning. The model includes vectors of incoming material fl ows, outgoing production fl ows and outgoing byproducts (production waste) described using appropriate formalizations. The authors provide the structural typifi cation of technological modules and subsystems for their mathematical analysis and subsequent digital transformation of livestock farms.

IMPROVEMENT OF STIV FOR VIDEO IMAGES CAPTURED UNDER DETERIORATED MEASUREMENT CONDITIONS

2018 ◽  
Vol 74 (5) ◽  
pp. I_619-I_624
Author(s):  
Ichiro FUJITA ◽  
Tatsushi SHIBANO ◽  
Kojiro TANI
Keyword(s):  
Video Images

scholarly journals On the use of plume models to estimate the flux in volcanic gas plumes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Julia Woitischek ◽  
Nicola Mingotti ◽  
Marie Edmonds ◽  
Andrew W. Woods
Keyword(s):  
Electrochemical Sensors ◽  
Measurement Techniques ◽  
Flux Measurement ◽  
Hydrothermal Systems ◽  
Mount Etna ◽  
Volcanic Gas ◽  
Gas Flux ◽  
Convective Structures ◽  
Video Images ◽  
Villarrica Volcano

AbstractMany of the standard volcanic gas flux measurement approaches involve absorption spectroscopy in combination with wind speed measurements. Here, we present a new method using video images of volcanic plumes to measure the speed of convective structures combined with classical plume theory to estimate volcanic fluxes. We apply the method to a nearly vertical gas plume at Villarrica Volcano, Chile, and a wind-blown gas plume at Mount Etna, Italy. Our estimates of the gas fluxes are consistent in magnitude with previous reported fluxes obtained by spectroscopy and electrochemical sensors for these volcanoes. Compared to conventional gas flux measurement techniques focusing on SO2, our new model also has the potential to be used for sulfur-poor plumes in hydrothermal systems because it estimates the H2O flux.

scholarly journals Low luminance visual acuity as a clinical measure and clinical trial outcome measure: a scoping review

2021 ◽  
Author(s):  
Laura J Wood ◽  
Jasleen K Jolly ◽  
Thomas MW Buckley ◽  
Amandeep S Josan ◽  
Robert E MacLaren
Keyword(s):  
Clinical Trial ◽  
Visual Acuity ◽  
Scoping Review ◽  
Outcome Measure ◽  
Clinical Measure ◽  
Trial Outcome ◽  
Clinical Trial Outcome ◽  
Low Luminance
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