Three-dimensional tracking of humans using very low-complexity radar

2006 ◽  
Vol 42 (18) ◽  
pp. 1062 ◽  
Author(s):  
A. Lin ◽  
H. Ling
Keyword(s):  
Three Dimensional ◽  
Low Complexity ◽  
Tracking Of Humans

scholarly journals A Low-Complexity Region-Based Authentication Algorithm for 3D Polygonal Models

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yuan-Yu Tsai ◽  
Tsung-Chieh Cheng ◽  
Yao-Hsien Huang
Keyword(s):  
Three Dimensional ◽  
Low Complexity ◽  
Secret Key ◽  
Authentication Code ◽  
Geometrical Properties ◽  
Property Evaluation ◽  
Adaptive Embedding ◽  
Local Properties ◽  
Embedding Rate ◽  
Polygonal Models

This study proposes a low-complexity region-based authentication algorithm for three-dimensional (3D) polygonal models, based on local geometrical property evaluation. A vertex traversal scheme with a secret key is adopted to classify each vertex into one of two categories: embeddable vertices and reference vertices. An embeddable vertex is one with an authentication code embedded. The algorithm then uses reference vertices to calculate local geometrical properties for the corresponding embeddable vertices. For each embeddable vertex, we feed the number of reference vertices and local properties into a hash function to generate the authentication code. The embeddable vertex is then embedded with the authentication code, which is based on a simple message-digit substitution scheme. The proposed algorithm is of low complexity and distortion-controllable and possesses a higher and more adaptive embedding capacity and a higher embedding rate than most existing region-based authentication algorithms for 3D polygonal models. The experimental results demonstrate the feasibility of the proposed algorithm.

scholarly journals Three-Dimensional Beamsteering Low-Complexity Reconfigurable Multilevel Antenna

2020 ◽  
Vol 19 (6) ◽  
pp. 1017-1021
Author(s):  
Ivan Zhou ◽  
German Augusto Ramirez ◽  
Luca Montero ◽  
Sebastian Blanch ◽  
Jordi Romeu ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Low Complexity

Low-complexity scalable distributed multicamera tracking of humans

2014 ◽  
Vol 10 (2) ◽  
pp. 1-32 ◽  
Author(s):  
Sebastian Gruenwedel ◽  
Vedran Jelaca ◽  
Jorge Oswaldo Nino-Castaneda ◽  
Peter van Hese ◽  
Dimitri van Cauwelaert ◽  
...  
Keyword(s):  
Low Complexity ◽  
Tracking Of Humans

scholarly journals Automated Simulation Framework for Urban Wind Environments Based on Aerial Point Clouds and Deep Learning

2021 ◽  
Vol 13 (12) ◽  
pp. 2383
Author(s):  
Chujin Sun ◽  
Fan Zhang ◽  
Pengju Zhao ◽  
Xinyi Zhao ◽  
Yuli Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cfd Simulation ◽  
Three Dimensional ◽  
Point Clouds ◽  
Local Area ◽  
Low Complexity ◽  
Target Area ◽  
Simulation Framework ◽  
Static Data ◽  
Automated Simulation

Computational fluid dynamics (CFD) simulation is a core component of wind engineering assessment for urban planning and architecture. CFD simulations require clean and low-complexity models. Existing modeling methods rely on static data from geographic information systems along with manual efforts. They are extraordinarily time-consuming and have difficulties accurately incorporating the up-to-date information of a target area into the flow model. This paper proposes an automated simulation framework with superior modeling efficiency and accuracy. The framework adopts aerial point clouds and an integrated two-dimensional and three-dimensional (3D) deep learning technique, with four operational modules: data acquisition and preprocessing, point cloud segmentation based on deep learning, geometric 3D reconstruction, and CFD simulation. The advantages of the framework are demonstrated through a case study of a local area in Shenzhen, China.

A Low Complexity Integrated Navigation System for Underwater Vehicles

2018 ◽  
Vol 71 (5) ◽  
pp. 1161-1177 ◽  
Author(s):  
Mehdi Emami ◽  
Mohammad Reza Taban
Keyword(s):  
Navigation System ◽  
Autonomous Underwater Vehicle ◽  
Three Dimensional ◽  
Low Complexity ◽  
Doppler Velocity ◽  
Integrated Navigation ◽  
Fusion Algorithm ◽  
Sea Trial ◽  
Integrated Navigation System ◽  
Computational Load

This paper proposes a simplified algorithm for reducing the computational load of the conventional underwater integrated navigation system. The system usually comprises a three-dimensional accelerometer, a three-dimensional gyroscope, a three-dimensional Doppler Velocity Log (DVL) and a data fusion algorithm, such as a Kalman Filter (KF). Since the expected variations of roll, pitch and depth are small, these quantities are assumed to be constant, and the proposed system is designed in a two-dimensional form. Due to the low speed of the vehicle, the nonlinear dynamic equation of the velocity can be simplified in a linear form. We also simplify the conventional KF in order to avoid matrix multiplications and matrix inversions. The performance of the designed system is evaluated in a sea trial by an Autonomous Underwater Vehicle (AUV). The results show that the proposed system can significantly reduce the computational load of the conventional integrated navigation system without a significant reduction in position and velocity accuracy.

Low-complexity sequences and single amino acid repeats: not just “junk” peptide sequences

Genome ◽  
2010 ◽  
Vol 53 (10) ◽  
pp. 753-762 ◽  
Author(s):  
Wilfried Haerty ◽  
G. Brian Golding
Keyword(s):  
Biological Function ◽  
Three Dimensional ◽  
Size Variation ◽  
Low Complexity ◽  
Single Amino Acid ◽  
Dimensional Structure ◽  
Three Dimensional Structure ◽  
Amino Acid Repeats ◽  
Eukaryotic Proteomes ◽  
Definition Of

For decades proteins were thought to interact in a “lock and key” system, which led to the definition of a paradigm linking stable three-dimensional structure to biological function. As a consequence, any non-structured peptide was considered to be nonfunctional and to evolve neutrally. Surprisingly, the most commonly shared peptides between eukaryotic proteomes are low-complexity sequences that in most conditions do not present a stable three-dimensional structure. However, because these sequences evolve rapidly and because the size variation of a few of them can have deleterious effects, low-complexity sequences have been suggested to be the target of selection. Here we review evidence that supports the idea that these simple sequences should not be considered just “junk” peptides and that selection drives the evolution of many of them.

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