CCD Implementation of a Three-Dimensional Video-Tracking Algorithm

1981 ◽  
Vol PAMI-3 (2) ◽  
pp. 230-240 ◽  
Author(s):  
R. M. Inigo ◽  
E. S. Mcvey
2014 ◽  
Vol 513-517 ◽  
pp. 1261-1267
Author(s):  
Jia Hong He ◽  
Xiao Ming Zhang ◽  
Yong Heng Wang

The three-dimensional spatial target tracking based on wireless communication technology has attracted more and more attention due to its importance in the field of Internet of Things.However,there are still some problems including calculation overhead is too high and power consumption is too large.Thus,a distributed three-dimensional target tracking mechanism for the environment of the Internet of Things is proposed.The network structure in the algorithm uses spatial clustering structure, which includes two tier sleep scheduling mechanisms and unite cluster head mechanism. A spatial segmental linear fitting method is adopted to track the target,which have effectively reduced the network overhead and improved tracking efficiency. It also provides a scheduling strategy how to wake up the sensor node guarantee to continue tracking it,when the mobile target lost.Simulation results show that the algorithm is better than the existing target tracking algorithm in tracking efficiency and have a lower power consumption.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Li Yang ◽  
Danshi Sun ◽  
Haote Ruan

In order to overcome the problems of the traditional algorithm, such as the time-consuming execution of acquisition instructions, low signal tracking accuracy, and low signal capture accuracy, a global satellite positioning receiver acquisition and tracking algorithm based on UWB technology is designed in this study. On the basis of expounding the pulse generation method and working principle in UWB technology, this paper analyzes in detail the characteristics of UWB technology, such as antimultipath, low power consumption, and strong penetration. Then, on the basis of window function filtering, in the process of three-dimensional search of global satellite positioning signal, firstly, the satellite signal entering the GPS software receiver is processed by RF front-end mixing and AD sampling, and then, the signal tracking and navigation message solving are completed according to the relationship between the influence factor and Doppler frequency offset. The experimental results show that the execution time of the acquisition instruction of the proposed algorithm varies between 1129 ms and 1617 ms; the signal tracking accuracy ranges between 0.931 and 0.951, and the signal capture accuracy ranges between 93.3% and 95.6%, which proves that the proposed algorithm has achieved the design expectation.


Author(s):  
Marianne M. Francois ◽  
Neil N. Carlson

Understanding the complex interaction of droplet dynamics with mass transfer and chemical reactions is of fundamental importance in liquid-liquid extraction. High-fidelity numerical simulation of droplet dynamics with interfacial mass transfer is particularly challenging because the position of the interface between the fluids and the interface physics need to be predicted as part of the solution of the flow equations. In addition, the discontinuity in fluid density, viscosity and species concentration at the interface present additional numerical challenges. In this work, we extend our balanced-force volume-tracking algorithm for modeling surface tension force (Francois et al., 2006) and we propose a global embedded interface formulation to model the interfacial conditions of an interface in thermodynamic equilibrium. To validate our formulation, we perform simulations of pure diffusion problems in one- and two-dimensions. Then we present two and three-dimensional simulations of a single droplet dynamics rising by buoyancy with mass transfer.


2020 ◽  
Vol 10 (2) ◽  
pp. 452-457
Author(s):  
Shen Jian ◽  
Chen Huan ◽  
Zuo Jianjian ◽  
Pan Xuming

Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) can track the brain nerve fiber and reconstruct non-invasively the three-dimensional image by tracing the local tensor orientation. The commonly used tracking method is usually based on the local diffusion information and insufficient to consider the geometrical structure and fractional anisotropy which is constrained by anatomical structure and physiological function of human. Therefore, a novel brain nerve fiber tracking algorithm based on Bayesian optical-flow constrained framework is proposed. The construction of energy function is the core step of global optical flow field estimation technology. In this paper, data fidelity constraint, prior constraint, penalty function and weight factor are introduced to construct Bayesian constraint function. The fiber trend model is displayed intuitively to obtain the structure and direction of the inner nerve fibers of the brain, which can better assist in the diagnosis and treatment of clinical brain diseases, and lay a foundation for subsequent brain tissue research.


2018 ◽  
Vol 77 (18) ◽  
pp. 24499-24519 ◽  
Author(s):  
Xi En Cheng ◽  
Shan Shan Du ◽  
Hui Ying Li ◽  
Jing Fang Hu ◽  
Ming Lu Chen

2018 ◽  
Vol 12 (5) ◽  
pp. 640-650 ◽  
Author(s):  
Howard Wang ◽  
Sing Kiong Nguang ◽  
Jiwei Wen

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