scholarly journals Natural hand posture determination using control-oriented inter-finger coordination kinematic models

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Nina Robson ◽  
Jong Seob Won
Keyword(s):  
Hand Posture ◽  
Kinematic Models

Interactions Between Hand Posture and Eye Movement

2013 ◽  
Author(s):  
Jihyun Suh ◽  
Richard A. Abrams
Keyword(s):  
Eye Movement ◽  
Hand Posture

Hand posture Recognition for shape variant hands

2011 ◽  
Vol 6 (4) ◽  
pp. 1-6
Author(s):  
Ayesha Butalia ◽  
◽  
A.K. Ramani ◽  
Parag Kulkarni ◽  
Swapnil Patil ◽  
...  
Keyword(s):  
Hand Posture ◽  
Hand Posture Recognition ◽  
Posture Recognition

The Effects of Keyboard Layout and Size on Smartphone Typing Performance

2020 ◽  
Vol 64 (1) ◽  
pp. 985-989
Author(s):  
Colton J. Turner ◽  
Barbara S. Chaparro ◽  
Inga M. Sogaard ◽  
Jibo He
Keyword(s):  
Error Rates ◽  
Hand Posture ◽  
Standard Keyboard ◽  
Keyboard Layout

Usability and typing performance on a smartphone with two unique QWERTY keyboard layouts (standard vs. curved) on two phone sizes (4.0-inch vs. 5.5-inch displays) was investigated in this study. The effect of hand posture was also investigated (one- vs. two-thumbs). Results show users typed the slowest when using one thumb with the curved keyboard on the small phone (15 WPM), and the fastest when using two thumbs with the standard keyboard on the large phone (24 WPM). Typing performance with the curved keyboard on the large phone size (19 WPM) did not differ between typing with one thumb using the standard keyboard on the large or small phone, or with two thumbs using the standard keyboard on the small phone. Error rates were higher when using the curved keyboard, regardless of phone size. Subjectively, the curved keyboard was rated inferior for both phone sizes in comparison to the standard layout.

scholarly journals Approach to hand posture recognition based on hand shape features for human–robot interaction

2021 ◽  
Author(s):  
Jing Qi ◽  
Kun Xu ◽  
Xilun Ding
Keyword(s):  
Gaussian Mixture ◽  
Human Robot Interaction ◽  
Polar Coordinates ◽  
Support Vector ◽  
Hand Posture ◽  
Data Set ◽  
Hand Shape ◽  
Hand Posture Recognition ◽  
Hand Segmentation ◽  
Posture Recognition

AbstractHand segmentation is the initial step for hand posture recognition. To reduce the effect of variable illumination in hand segmentation step, a new CbCr-I component Gaussian mixture model (GMM) is proposed to detect the skin region. The hand region is selected as a region of interest from the image using the skin detection technique based on the presented CbCr-I component GMM and a new adaptive threshold. A new hand shape distribution feature described in polar coordinates is proposed to extract hand contour features to solve the false recognition problem in some shape-based methods and effectively recognize the hand posture in cases when different hand postures have the same number of outstretched fingers. A multiclass support vector machine classifier is utilized to recognize the hand posture. Experiments were carried out on our data set to verify the feasibility of the proposed method. The results showed the effectiveness of the proposed approach compared with other methods.

scholarly journals ASKAP observations of multiple rapid scintillators reveal a degrees-long plasma filament

2021 ◽  
Vol 502 (3) ◽  
pp. 3294-3311
Author(s):  
Yuanming Wang ◽  
Artem Tuntsov ◽  
Tara Murphy ◽  
Emil Lenc ◽  
Mark Walker ◽  
...  
Keyword(s):  
Physical Properties ◽  
Angular Width ◽  
Scattering Medium ◽  
Central Frequency ◽  
Linear Arrangement ◽  
Plasma Filament ◽  
Kinematic Models ◽  
Tidal Stream ◽  
First Time ◽  
Insight Into

ABSTRACT We present the results from an Australian Square Kilometre Array Pathfinder search for radio variables on timescales of hours. We conducted an untargeted search over a 30 deg2 field, with multiple 10-h observations separated by days to months, at a central frequency of 945 MHz. We discovered six rapid scintillators from 15-min model-subtracted images with sensitivity of $\sim\! 200\, \mu$Jy/beam; two of them are extreme intra-hour variables with modulation indices up to $\sim 40{{\ \rm per\ cent}}$ and timescales as short as tens of minutes. Five of the variables are in a linear arrangement on the sky with angular width ∼1 arcmin and length ∼2 degrees, revealing the existence of a huge plasma filament in front of them. We derived kinematic models of this plasma from the annual modulation of the scintillation rate of our sources, and we estimated its likely physical properties: a distance of ∼4 pc and length of ∼0.1 pc. The characteristics we observe for the scattering screen are incompatible with published suggestions for the origin of intra-hour variability leading us to propose a new picture in which the underlying phenomenon is a cold tidal stream. This is the first time that multiple scintillators have been detected behind the same plasma screen, giving direct insight into the geometry of the scattering medium responsible for enhanced scintillation.

scholarly journals Lateral resistance of mass timber shear wall connected by withdrawal-type connectors

2021 ◽  
Vol 67 (1) ◽  
Author(s):  
Sung-Jun Pang ◽  
Kyung-Sun Ahn ◽  
Seog Goo Kang ◽  
Jung-Kwon Oh
Keyword(s):  
Experimental Data ◽  
Seismic Design ◽  
Shear Walls ◽  
Shear Wall ◽  
Vertical Load ◽  
Lateral Resistance ◽  
Kinematic Models ◽  
Mass Timber ◽  
Timber Shear Walls ◽  
Timber Shear Wall

AbstractIn this study, the lateral resistances of mass timber shear walls were investigated for seismic design. The lateral resistances were predicted by kinematic models with mechanical properties of connectors, and compared with experimental data. Four out of 7 shear wall specimens consisted of a single Ply-lam panel and withdrawal-type connectors. Three out of 7 shear wall specimens consisted of two panels made by dividing a single panel in half. The divided panels were connected by 2 or 4 connectors like a single panel before being divided. The applied vertical load was 0, 24, or 120 kN, and the number of connectors for connecting the Ply-lam wall-to-floor was 2 or 4. As a result, the tested data were 6.3 to 52.7% higher than the predicted value by kinematic models, and it means that the lateral resistance can be designed by the behavior of the connector, and the prediction will be safe. The effects of wall-to-wall connectors, wall-to-floor connectors and vertical loads on the shear wall were analyzed with the experimental data.

scholarly journals Human and bird detection and classification based on Doppler radar spectrograms and vision images using convolutional neural networks

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110105
Author(s):  
Jnana Sai Abhishek Varma Gokaraju ◽  
Weon Keun Song ◽  
Min-Ho Ka ◽  
Somyot Kaitwanidvilai
Keyword(s):  
Neural Networks ◽  
Object Recognition ◽  
Convolutional Neural Networks ◽  
Doppler Radar ◽  
Autonomous Vehicle ◽  
Sampling Point ◽  
Body Segment ◽  
Kinematic Modeling ◽  
Deep Convolutional Neural Networks ◽  
Kinematic Models

The study investigated object detection and classification based on both Doppler radar spectrograms and vision images using two deep convolutional neural networks. The kinematic models for a walking human and a bird flapping its wings were incorporated into MATLAB simulations to create data sets. The dynamic simulator identified the final position of each ellipsoidal body segment taking its rotational motion into consideration in addition to its bulk motion at each sampling point to describe its specific motion naturally. The total motion induced a micro-Doppler effect and created a micro-Doppler signature that varied in response to changes in the input parameters, such as varying body segment size, velocity, and radar location. Micro-Doppler signature identification of the radar signals returned from the target objects that were animated by the simulator required kinematic modeling based on a short-time Fourier transform analysis of the signals. Both You Only Look Once V3 and Inception V3 were used for the detection and classification of the objects with different red, green, blue colors on black or white backgrounds. The results suggested that clear micro-Doppler signature image-based object recognition could be achieved in low-visibility conditions. This feasibility study demonstrated the application possibility of Doppler radar to autonomous vehicle driving as a backup sensor for cameras in darkness. In this study, the first successful attempt of animated kinematic models and their synchronized radar spectrograms to object recognition was made.

scholarly journals Collision Avoidance and Stability Study of a Self-Reconfigurable Drainage Robot

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3744
Author(s):  
Rizuwana Parween ◽  
M. A. Viraj J. Muthugala ◽  
Manuel V. Heredia ◽  
Karthikeyan Elangovan ◽  
Mohan Rajesh Elara
Keyword(s):  
Collision Avoidance ◽  
Mechanical Design ◽  
Side Wall ◽  
Stability Study ◽  
Directional Movement ◽  
Kinematic Models ◽  
Wall Collision ◽  
Inspection And Maintenance ◽  
Rolling Wheel ◽  
Hybrid Locomotion

The inspection and maintenance of drains with varying heights necessitates a drain mapping robot with trained labour to maintain community hygiene and prevent the spread of diseases. For adapting to level changes and navigating in the narrow confined environments of drains, we developed a self-configurable hybrid robot, named Tarantula-II. The platform is a quadruped robot with hybrid locomotion and the ability to reconfigure to achieve variable height and width. It has four legs, and each leg is made of linear actuators and modular rolling wheel mechanisms with bi-directional movement. The platform has a fuzzy logic system for collision avoidance of the side wall in the drain environment. During level shifting, the platform achieves stability by using the pitch angle as the feedback from the inertial measuring unit (IMU) mounted on the platform. This feedback helps to adjust the accurate height of the platform. In this paper, we describe the detailed mechanical design and system architecture, kinematic models, control architecture, and stability of the platform. We deployed the platform both in a lab setting and in a real-time drain environment to demonstrate the wall collision avoidance, stability, and level shifting capabilities of the platform.

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