Fusing Real-Time Depth Imaging with High Precision Pose Estimation by a Measurement Arm

2012 ◽  
Author(s):  
Svenja Kahn ◽  
Arjan Kuijper
Keyword(s):  
Real Time ◽  
High Precision ◽  
Pose Estimation ◽  
Depth Imaging

scholarly journals Fast High-Precision Electrical Impedance Tomography System for Real-Time Perfusion Imaging

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 61570-61580 ◽  
Author(s):  
Weichen Li ◽  
Junying Xia ◽  
Ge Zhang ◽  
Hang Ma ◽  
Benyuan Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Electrical Impedance Tomography ◽  
High Precision ◽  
Perfusion Imaging ◽  
Electrical Impedance ◽  
Impedance Tomography ◽  
Tomography System

scholarly journals High-precision and cost-efficient sequencing for real-time COVID-19 surveillance

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Yong Park ◽  
Gina Faraci ◽  
Pamela M. Ward ◽  
Jane F. Emerson ◽  
Ha Youn Lee
Keyword(s):  
Los Angeles ◽  
Whole Genome Sequencing ◽  
Real Time ◽  
Genome Sequencing ◽  
High Precision ◽  
High Throughput Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Public Health Response ◽  
Cost Efficient

AbstractCOVID-19 global cases have climbed to more than 33 million, with over a million total deaths, as of September, 2020. Real-time massive SARS-CoV-2 whole genome sequencing is key to tracking chains of transmission and estimating the origin of disease outbreaks. Yet no methods have simultaneously achieved high precision, simple workflow, and low cost. We developed a high-precision, cost-efficient SARS-CoV-2 whole genome sequencing platform for COVID-19 genomic surveillance, CorvGenSurv (Coronavirus Genomic Surveillance). CorvGenSurv directly amplified viral RNA from COVID-19 patients’ Nasopharyngeal/Oropharyngeal (NP/OP) swab specimens and sequenced the SARS-CoV-2 whole genome in three segments by long-read, high-throughput sequencing. Sequencing of the whole genome in three segments significantly reduced sequencing data waste, thereby preventing dropouts in genome coverage. We validated the precision of our pipeline by both control genomic RNA sequencing and Sanger sequencing. We produced near full-length whole genome sequences from individuals who were COVID-19 test positive during April to June 2020 in Los Angeles County, California, USA. These sequences were highly diverse in the G clade with nine novel amino acid mutations including NSP12-M755I and ORF8-V117F. With its readily adaptable design, CorvGenSurv grants wide access to genomic surveillance, permitting immediate public health response to sudden threats.

scholarly journals LOCUS: A Multi-Sensor Lidar-Centric Solution for High-Precision Odometry and 3D Mapping in Real-Time

2021 ◽  
Vol 6 (2) ◽  
pp. 421-428
Author(s):  
Matteo Palieri ◽  
Benjamin Morrell ◽  
Abhishek Thakur ◽  
Kamak Ebadi ◽  
Jeremy Nash ◽  
...  
Keyword(s):  
Real Time ◽  
High Precision ◽  
3D Mapping

High-precision roll attitude estimation of decoupled canards relative to the projectile body using bipolar hall-effect sensors

2021 ◽  
pp. 1-9
Author(s):  
Tingting Yin ◽  
Zhong Yang ◽  
Youlong Wu ◽  
Fangxiu Jia
Keyword(s):  
Hall Effect ◽  
Real Time ◽  
High Precision ◽  
Solution Method ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Attitude Estimation ◽  
Fuzzy Algorithms ◽  
Positioning Method ◽  
Hall Effect Sensors

The high-precision roll attitude estimation of the decoupled canards relative to the projectile body based on the bipolar hall-effect sensors is proposed. Firstly, the basis engineering positioning method based on the edge detection is introduced. Secondly, the simplified dynamic relative roll model is established where the feature parameters are identified by fuzzy algorithms, while the high-precision real-time relative roll attitude estimation algorithm is proposed. Finally, the trajectory simulations and grounded experiments have been conducted to evaluate the advantages of the proposed method. The positioning error is compared with the engineering solution method, and it is proved that the proposed estimation method has the advantages of the high accuracy and good real-time performance.

scholarly journals Robust hand gesture recognition using multiple shape-oriented visual cues

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Samy Bakheet ◽  
Ayoub Al-Hamadi
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Pose Estimation ◽  
Depth Map ◽  
Hand Gesture Recognition ◽  
Support Vector ◽  
Hand Gesture ◽  
Hand Pose Estimation ◽  
Time Operation ◽  
Hand Pose

AbstractRobust vision-based hand pose estimation is highly sought but still remains a challenging task, due to its inherent difficulty partially caused by self-occlusion among hand fingers. In this paper, an innovative framework for real-time static hand gesture recognition is introduced, based on an optimized shape representation build from multiple shape cues. The framework incorporates a specific module for hand pose estimation based on depth map data, where the hand silhouette is first extracted from the extremely detailed and accurate depth map captured by a time-of-flight (ToF) depth sensor. A hybrid multi-modal descriptor that integrates multiple affine-invariant boundary-based and region-based features is created from the hand silhouette to obtain a reliable and representative description of individual gestures. Finally, an ensemble of one-vs.-all support vector machines (SVMs) is independently trained on each of these learned feature representations to perform gesture classification. When evaluated on a publicly available dataset incorporating a relatively large and diverse collection of egocentric hand gestures, the approach yields encouraging results that agree very favorably with those reported in the literature, while maintaining real-time operation.

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