PTZ camera-based adaptive panoramic and multi-layered background model

Author(s):  
Kang Xue ◽  
Gbolabo Ogunmakin ◽  
Yue Liu ◽  
Patricio A. Vela ◽  
Yongtian Wang
Keyword(s):  
2018 ◽  
Vol 12 (4) ◽  
pp. 32
Author(s):  
SANTOSH DADI HARIHARA ◽  
KRISHNA MOHAN PILLUTLA GOPALA ◽  
LATHA MAKKENA MADHAVI ◽  
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◽  
...  

2013 ◽  
Vol 39 (10) ◽  
pp. 1674
Author(s):  
Dong YANG ◽  
Xiu-Ling ZHOU ◽  
Ping GUO

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
T. Abrahão ◽  
◽  
H. Almazan ◽  
J. C. dos Anjos ◽  
S. Appel ◽  
...  

Abstract A θ13 oscillation analysis based on the observed antineutrino rates at the Double Chooz far and near detectors for different reactor power conditions is presented. This approach provides a so far unique simultaneous determination of θ13 and the total background rates without relying on any assumptions on the specific background contributions. The analysis comprises 865 days of data collected in both detectors with at least one reactor in operation. The oscillation results are enhanced by the use of 24.06 days (12.74 days) of reactor-off data in the far (near) detector. The analysis considers the $$ {\overline{\nu}}_e $$ ν ¯ e interactions up to a visible energy of 8.5 MeV, using the events at higher energies to build a cosmogenic background model considering fast-neutrons interactions and 9Li decays. The background-model-independent determination of the mixing angle yields sin2(2θ13) = 0.094 ± 0.017, being the best-fit total background rates fully consistent with the cosmogenic background model. A second oscillation analysis is also performed constraining the total background rates to the cosmogenic background estimates. While the central value is not significantly modified due to the consistency between the reactor-off data and the background estimates, the addition of the background model reduces the uncertainty on θ13 to 0.015. Along with the oscillation results, the normalization of the anti-neutrino rate is measured with a precision of 0.86%, reducing the 1.43% uncertainty associated to the expectation.


Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. E201-E212 ◽  
Author(s):  
Jochen Kamm ◽  
Michael Becken ◽  
Laust B. Pedersen

We present an efficient approximate inversion scheme for near-surface loop-loop EM induction data (slingram) that can be applied to obtain 2D or 3D models on a normal desktop computer. Our approach is derived from a volume integral equation formulation with an arbitrarily conductive homogeneous half-space as a background model. The measurements are not required to fulfill the low induction number condition (low frequency and conductivity). The high efficiency of the method is achieved by invoking the Born approximation around a half-space background. The Born approximation renders the forward operator linear. The choice of a homogeneous half-space yields closed form expressions for the required electromagnetic normal fields. It also yields a translationally invariant forward operator, i.e., a highly redundant Jacobian. In connection with the application of a matrix-free conjugate gradient method, this allows for very low memory requirements during the inversion, even in three dimensions. As a consequence of the Born approximation, strong conductive deviations from the background model are underestimated. Highly resistive anomalies are in principle overestimated, but at the same time difficult to resolve with induction methods. In the case of extreme contrasts, our forward model may fail in simultaneously explaining all the data collected. We applied the method to EM34 data from a profile that has been extensively studied with other electromagnetic methods and compare the results. Then, we invert three conductivity maps from the same area in a 3D inversion.


2015 ◽  
Vol 734 ◽  
pp. 203-206
Author(s):  
En Zeng Dong ◽  
Sheng Xu Yan ◽  
Kui Xiang Wei

In order to enhance the rapidity and the accuracy of moving target detection and tracking, and improve the speed of the algorithm on the DSP (digital signal processor), an active visual tracking system was designed based on the gaussian mixture background model and Meanshift algorithm on DM6437. The system use the VLIB library developed by TI, and through the method of gaussian mixture background model to detect the moving objects and use the Meanshift tracking algorithm based on color features to track the target in RGB space. Finally, the system is tested on the hardware platform, and the system is verified to be quickness and accuracy.


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