Debing Zeng

Dr. Debing Zeng


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 January 2016 in Sensors
Verified
Journal Article
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FZFuqiang Zhou
Fuqiang Zhou
HHHuabin He
Huabin He
DZDebing Zeng
Debing Zeng
Global calibration methods for multi-camera system are critical to the accuracy of vision measurement. Proposed in this paper is such a method based on several groups of sphere targets and a precision auxiliary camera. Each camera to be calibrated observes a group of spheres (at least three), while the auxiliary camera observes all the spheres. The global calibration can be achieved after each camera reconstructs the sphere centers in its field of view. In the process of reconstructing a sphere center, a parameter equation is used to describe the sphere projection model. Theoretical analysis and computer simulation are carried out to analyze the factors that affect the calibration accuracy. Simulation results show that the parameter equation can largely improve the reconstruction accuracy. In the experiments, a two-camera system calibrated by our method is used to measure a distance about 578 mm, and the root mean squared error is within 0.14 mm. Furthermore, the experiments indicate that the method has simple operation and good flexibility, especially for the onsite multiple cameras without common field of view.

4 June 2021 in Scientific Reports
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Journal Article
Open access
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RCRafael Carballeira
Rafael Carballeira
DDDavid Dolgitzer
David Dolgitzer
PZPeng Zhao
Peng Zhao
DZDebing Zeng
Debing Zeng
YCYusui Chen
Yusui Chen
We derive the evolution equations for two-time correlation functions of a generalized non-Markovian open quantum system based on a modified stochastic Schrödinger equation approach. We find that the two-time reduced propagator, an object that used to be characterized by two independent stochastic processes in the Hilbert space of the system, can be simplified and obtained by taking ensemble average over one single noise. This discovery can save the cost of computation, and accelerate the converging process when taking the average over noisy trajectories. As a result, our method can be widely applied to many open quantum models, especially large-scale systems and extend the quantum regression theory to the non-Markovian case. In the short-time simulations, it is observed a significant difference between Markovian and non-Markovian cases, which can be applied to realize the environmental spectrum detection and enhance the measurement sensitivity in varying open quantum systems.