scholarly journals Computer Vision for 3D Perception and Applications

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3944
Author(s):  
Matteo Poggi ◽  
Thomas B. Moeslund
Keyword(s):  
Computer Vision ◽  
3D Perception ◽  
Surrounding Environment ◽  
High Level

Effective 3D perception of an observed scene greatly enriches the knowledge about the surrounding environment and is crucial to effectively develop high-level applications for various purposes [...]

scholarly journals Analysis of Occlusion Effects for Map-Based Self-Localization in Urban Areas

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5196
Author(s):  
Yuki Endo ◽  
Ehsan Javanmardi ◽  
Shunsuke Kamijo
Keyword(s):  
Urban Areas ◽  
Structural Information ◽  
Average Error ◽  
High Definition ◽  
Geometrical Structures ◽  
Real Environment ◽  
Surrounding Environment ◽  
Localization Errors ◽  
Stable Estimation ◽  
High Level

A high-definition (HD) map provides structural information for map-based self-localization, enabling stable estimation in real environments. In urban areas, there are many obstacles, such as buses, that occlude sensor observations, resulting in self-localization errors. However, most of the existing HD map-based self-localization evaluations do not consider sudden significant errors due to obstacles. Instead, they evaluate this in terms of average error over estimated trajectories in an environment with few occlusions. This study evaluated the effects of self-localization estimation on occlusion with synthetically generated obstacles in a real environment. Various patterns of synthetic occlusion enabled the analyses of the effects of self-localization error from various angles. Our experiments showed various characteristics that locations susceptible to obstacles have. For example, we found that occlusion in intersections tends to increase self-localization errors. In addition, we analyzed the geometrical structures of a surrounding environment in high-level error cases and low-level error cases with occlusions. As a result, we suggested the concept that the real environment should have to achieve robust self-localization under occlusion conditions.

scholarly journals Visual Behavior Based Bio-Inspired Polarization Techniques in Computer Vision and Robotics

2012 ◽  
pp. 243-272 ◽  
Author(s):  
Abd El Rahman Shabayek ◽  
Olivier Morel ◽  
David Fofi
Keyword(s):  
Computer Vision ◽  
Object Recognition ◽  
Visual Perception ◽  
Polarization Vision ◽  
Visual Behavior ◽  
Biologically Inspired ◽  
Long Time ◽  
Comprehensive Survey ◽  
High Level ◽  
And Robotics

For long time, it was thought that the sensing of polarization by animals is invariably related to their behavior, such as navigation and orientation. Recently, it was found that polarization can be part of a high-level visual perception, permitting a wide area of vision applications. Polarization vision can be used for most tasks of color vision including object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. The polarization based visual behavior found in the animal kingdom is briefly covered. Then, the authors go in depth with the bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization based techniques and how they are biologically inspired.

Learning human poses in natural scenes

2018 ◽  
Author(s):  
◽  
Guanghan Ning
Keyword(s):  
Computer Vision ◽  
Pose Estimation ◽  
The Body ◽  
Human Pose Estimation ◽  
Natural Scenes ◽  
Top Down ◽  
University Of Missouri ◽  
Single Person ◽  
Human Pose ◽  
High Level

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The task of human pose estimation in natural scenes is to determine the precise pixel locations of body keypoints. It is very important for many high-level computer vision tasks, including action and activity recognition, human-computer interaction, motion capture, and animation. We cover two different approaches for this task: top-down approach and bottom-up approach. In the top-down approach, we propose a human tracking method called ROLO that localizes each person. We then propose a state-of-the-art single-person human pose estimator that predicts the body keypoints of each individual. In the bottomup approach, we propose an efficient multi-person pose estimator with which we participated in a PoseTrack challenge [11]. On top of these, we propose to employ adversarial training to further boost the performance of single-person human pose estimator while generating synthetic images. We also propose a novel PoSeg network that jointly estimates the multi-person human poses and semantically segment the portraits of these persons at pixel-level. Lastly, we extend some of the proposed methods on human pose estimation and portrait segmentation to the task of human parsing, a more finegrained computer vision perception of humans.

scholarly journals The polar sea ice topography reconstruction system

2020 ◽  
Vol 61 (82) ◽  
pp. 127-138
Author(s):  
Scott Sorensen ◽  
Vinit Veerendraveer ◽  
Wayne Treible ◽  
Andrew R. Mahoney ◽  
Chandra Kambhamettu
Keyword(s):  
Computer Vision ◽  
Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Camera System ◽  
Melt Pond ◽  
Camera Systems ◽  
Ice Concentration ◽  
Level Information ◽  
High Level

AbstractThe Polar Sea Ice Topography REconstruction System, or PSITRES, is a 3D camera system designed to continuously monitor an area of ice and water adjacent to an ice-going vessel. Camera systems aboard ships in the polar regions are common; however, the application of computer vision techniques to extract high-level information from the imagery is infrequent. Many of the existing systems are built for human involvement throughout the process and lack automation necessary for round the clock use. The PSITRES was designed with computer vision in mind. It can capture images continuously for days on end with limited oversight. We have applied the system in different ice observing scenarios. The PSITRES was deployed on three research expeditions in the Arctic and Subarctic, and we present applications in measuring ice concentration, melt pond fraction and presence of algae. Systems like PSITRES and the computer vision algorithms applied represent steps toward automatically observing, evaluating and analyzing ice and the environment around ships in ice-covered waters.

scholarly journals Vision based supervised restricted Boltzmann machine helps to actuate novel shape memory alloy accurately

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ritaban Dutta ◽  
Cherry Chen ◽  
David Renshaw ◽  
Daniel Liang
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Shape Memory ◽  
Video Data ◽  
The Body ◽  
Restricted Boltzmann Machine ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Boltzmann Machine ◽  
High Level

AbstractExtraordinary shape recovery capabilities of shape memory alloys (SMAs) have made them a crucial building block for the development of next-generation soft robotic systems and associated cognitive robotic controllers. In this study we desired to determine whether combining video data analysis techniques with machine learning techniques could develop a computer vision based predictive system to accurately predict force generated by the movement of a SMA body that is capable of a multi-point actuation performance. We identified that rapid video capture of the bending movements of a SMA body while undergoing external electrical excitements and adapting that characterisation using computer vision approach into a machine learning model, can accurately predict the amount of actuation force generated by the body. This is a fundamental area for achieving a superior control of the actuation of SMA bodies. We demonstrate that a supervised machine learning framework trained with Restricted Boltzmann Machine (RBM) inspired features extracted from 45,000 digital thermal infrared video frames captured during excitement of various SMA shapes, is capable to estimate and predict force and stress with 93% global accuracy with very low false negatives and high level of predictive generalisation.

scholarly journals Risk factors for domestic infestation by the Chagas disease vector, Triatoma dimidiata in Chiquimula, Guatemala

2013 ◽  
Vol 103 (6) ◽  
pp. 634-643 ◽  
Author(s):  
E. N. I. Weeks ◽  
C. Cordón-Rosales ◽  
C. Davies ◽  
S. Gezan ◽  
M. Yeo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Chagas Disease ◽  
Current Method ◽  
Cost Effective ◽  
Subsequent Treatment ◽  
Disease Vector ◽  
Surrounding Environment ◽  
Increased Risk ◽  
High Level ◽  
House Infestation

AbstractIn Guatemala prior to control initiatives, the main vectors of Trypanosoma cruzi, the causative agent of Chagas disease, were Rhodnius prolixus and Triatoma dimidiata. This study conducted in 2006 in the department of Chiquimula recorded a high level of T. dimidiata infestation and an absence of R. prolixus in all surveyed communities. In Guatemala, the presence of T. dimidiata as domestic, peridomestic and sylvatic populations results in control difficulties as houses are re-infested from the surrounding environment. Entomological surveys, the current method used to select houses in need of control efforts, are labour intensive and time consuming. A time- and cost-effective way to prioritize houses for evaluation and subsequent treatment is the stratification of houses based on the risk of triatomine infestation. In the present study, 17 anthropogenic risk factors were evaluated for associations with house infestation of T. dimidiata including: wall, floor and roof type. There was an increased likelihood of domestic infestation with T. dimidiata associated with the presence of dirt floors (18/29; OR 8.075, 95% CI 2.13–30.6), uncoated bajareque walls (12/17; OR 4.80, 95% CI 1.35–17.1) and triatomine-like faeces on walls (16/26; OR 3.89, 95% CI 1.19–12.7). These factors could be used to target control of T. dimidiata to communities with an increased risk of being infested.

scholarly journals Computer Vision

2021 ◽  
Vol 9 (VII) ◽  
pp. 1237-1239
Author(s):  
Omkar Madhukar Deshmukh
Keyword(s):  
Computer Vision ◽  
Sensory System ◽  
Image Understanding ◽  
Scientific Field ◽  
High Dimensional ◽  
Thought Processes ◽  
Knowledge Domain ◽  
Nursing Knowledge ◽  
Pure Mathematics ◽  
High Level

Computer vision may be a field of computer science that trains computers to interpret and perceive the visual world. exploitation digital pictures from cameras and videos and deep learning models, machines will accurately determine and classify objects — and so react to what they "see.”. Computer vision is Associate in Nursing knowledge domain scientific field that deals with however computers will gain high-level understanding from digital pictures or videos. From the angle of engineering, it seeks to grasp and alter tasks that the human sensory system will do. Computer vision tasks embrace strategies for exploit, processing, analyzing and understanding digital pictures, and extraction of high-dimensional knowledge from the important world so as to supply numerical or symbolic info, e.g. within the styles of selections. Understanding during this context suggests that the transformation of visual pictures (the input of the retina) into descriptions of the planet that be to thought processes and might elicit acceptable action. This image understanding will be seen because the disentangling of symbolic info from image knowledge mistreatment models created with the help of pure mathematics, physics, statistics, and learning theory.

scholarly journals The ecological role of Accipitridae vultures in terrestrial landscapes of Azerbaijan

2020 ◽  
Vol 10 (1) ◽  
pp. 90-94
Author(s):  
T. Karimov ◽  
A. Matsyura
Keyword(s):  
Total Population ◽  
Point Of View ◽  
Wild Animals ◽  
Wild Mammals ◽  
Source Of Infection ◽  
Surrounding Environment ◽  
Difficult Terrain ◽  
High Level ◽  
Sanitary Conditions

Scavengers can provide ecosystem services to people by removal of dead animals that could become sources of disease. From such point of view, it seems appropriate to evaluate these benefits in Azerbaijan in quantitative terms. To this end, in 2013, an extensive monitoring was organized in the Turyanchay Reserve, which covers six regions and neighboring territories (the total population here is 640 thousand people). A high level of animal mortality in the Turyanchay Reserve is supported by the concentration of 24 species of wild mammals and 700 thousand domestic animals in the surrounding environment. The difficult terrain area is another factor leading to the death of animals. Animals grazing on hillsides often break down and die. The bodies of domestic and wild animals killed by wolves also often remain lying on this territory. In addition, vehicles traveling along the Agdash-Gabala highway cause the death of many domestic and wild animals. During the two months of the study (from June to July), 62 dead animals were found. Ten kinds of diseases were identified in 38 undecomposed bodies of these animals. Scavengers eat animal bodies in one-three days (without bones), preventing them from becoming a source of infection. The role of necrophages in minimizing of epizootic cases and improving sanitary conditions is important for ecosystems, because the blood of most animals is a carrier of diseases and most of the parasites present in it are common to both humans and animals. Scavengers can be used by veterinary organizations as indicators to simplify the identification of animal bodies and the subsequent disposal of their remains.

scholarly journals MEASURING THE SWAY OF IMPERCEPTIBLE FACTORS IN SHAPING THE DISTINCT CHARACTER OF ANCIENT INDIAN ARCHITECTURE AND CITY PLANNING

2018 ◽  
Vol 16 ◽  
Author(s):  
Tamara Kelly
Keyword(s):  
City Planning ◽  
Indian Philosophy ◽  
Great Element ◽  
Human Needs ◽  
Indian Architecture ◽  
Human Scale ◽  
Surrounding Environment ◽  
Distinct Character ◽  
High Level ◽  
The Impact

In India, great obey to nature is evident in architecture, and the essence of life is fairly apparent in city planning. Human kind reflects his perception of life in architecture by locating the spaces within the dwelling in particular order to ensure great harmony with positive and negative forces of the cosmos. Modern architecture shaped by political and economic factors resulted in sameness among most of contemporary capitals or developments, ignoring farming and human needs that has caused decays in urban fabric, and resulting in high level of gas emissions in mega cities. By contrast, ancient architecture in India connects the occupants with surrounding environment and ensure harmony between humans and nature through many aspects, and scale is a great element being considered in space and city planning leading into the Mandala graph. In Indian philosophy, disproportion and detachment of mankind from nature and surrounding environment lead to disaster. Hence, the Mandala diagram addresses all the existence taking into account farming, human scale and needs. The purpose of this research is to examine the impact of intangible factors such as traditional beliefs and religions in shaping the astonishing character of Indian architecture. Furthermore, it delves ino many metaphysic theories to test their influences on evolving the Mandala diagram and the logic behind the distribution of functions within its parts.

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