7,284 research outputs found
Good Features to Correlate for Visual Tracking
During the recent years, correlation filters have shown dominant and
spectacular results for visual object tracking. The types of the features that
are employed in these family of trackers significantly affect the performance
of visual tracking. The ultimate goal is to utilize robust features invariant
to any kind of appearance change of the object, while predicting the object
location as properly as in the case of no appearance change. As the deep
learning based methods have emerged, the study of learning features for
specific tasks has accelerated. For instance, discriminative visual tracking
methods based on deep architectures have been studied with promising
performance. Nevertheless, correlation filter based (CFB) trackers confine
themselves to use the pre-trained networks which are trained for object
classification problem. To this end, in this manuscript the problem of learning
deep fully convolutional features for the CFB visual tracking is formulated. In
order to learn the proposed model, a novel and efficient backpropagation
algorithm is presented based on the loss function of the network. The proposed
learning framework enables the network model to be flexible for a custom
design. Moreover, it alleviates the dependency on the network trained for
classification. Extensive performance analysis shows the efficacy of the
proposed custom design in the CFB tracking framework. By fine-tuning the
convolutional parts of a state-of-the-art network and integrating this model to
a CFB tracker, which is the top performing one of VOT2016, 18% increase is
achieved in terms of expected average overlap, and tracking failures are
decreased by 25%, while maintaining the superiority over the state-of-the-art
methods in OTB-2013 and OTB-2015 tracking datasets.Comment: Accepted version of IEEE Transactions on Image Processin
Iterative Time-Varying Filter Algorithm Based on Discrete Linear Chirp Transform
Denoising of broadband non--stationary signals is a challenging problem in
communication systems. In this paper, we introduce a time-varying filter
algorithm based on the discrete linear chirp transform (DLCT), which provides
local signal decomposition in terms of linear chirps. The method relies on the
ability of the DLCT for providing a sparse representation to a wide class of
broadband signals. The performance of the proposed algorithm is compared with
the discrete fractional Fourier transform (DFrFT) filtering algorithm.
Simulation results show that the DLCT algorithm provides better performance
than the DFrFT algorithm and consequently achieves high quality filtering.Comment: 6 pages, conference pape
Does more intense competition lead to higher growth?
The relationship between the intensity of competition in an economy and its long-run growth is an open question in economics. Theoretically, there is no clear-cut answer. Empirical evidence exists, however, that in some sectors more competition leads to more innovation, and accelerates productivity growth. To complement those findings, and capture economy-wide effects, the authors conduct a cross-country study. They examine the impact on growth of various measures having to do with intensity of domestic competition - beyond the effects of trade liberalization. Their results indicate a strong correlation between long-run growth, and effective enforcement of antitrust, and competition policy.Environmental Economics&Policies,Economic Theory&Research,ICT Policy and Strategies,Labor Policies,Decentralization,Economic Theory&Research,Environmental Economics&Policies,ICT Policy and Strategies,Achieving Shared Growth,Governance Indicators
Environmental urbanization assessment using gis and multicriteria decision analysis: a case study for Denizli (Turkey) municipal area
In recent years, life quality of the urban areas is a growing interest of civil engineering. Environmental quality is essential to display the position of sustainable development and asserts the corresponding countermeasures to the protection of environment. Urban environmental quality involves multidisciplinary parameters and difficulties to be analyzed. The problem is not only complex but also involves many uncertainties, and decision-making on these issues is a challenging problem which contains many parameters and alternatives inherently. Multicriteria decision analysis (MCDA) is a very prepotent technique to solve that sort of problems, and it guides the users confidence by synthesizing that information. Environmental concerns frequently contain spatial information. Spatial multicriteria decision analysis (SMCDA) that includes Geographic Information System (GIS) is efficient to tackle that type of problems. This study has employed some geographic and urbanization parameters to assess the environmental urbanization quality used by those methods. The study area has been described in five categories: very favorable, favorable, moderate, unfavorable, and very unfavorable. The results are momentous to see the current situation, and they could help to mitigate the related concerns. The study proves that the SMCDA descriptions match the environmental quality perception in the city. © 2018 Erdal Akyol et al
Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters
Segmentation of an object from a video is a challenging task in multimedia
applications. Depending on the application, automatic or interactive methods
are desired; however, regardless of the application type, efficient computation
of video object segmentation is crucial for time-critical applications;
specifically, mobile and interactive applications require near real-time
efficiencies. In this paper, we address the problem of video segmentation from
the perspective of efficiency. We initially redefine the problem of video
object segmentation as the propagation of MRF energies along the temporal
domain. For this purpose, a novel and efficient method is proposed to propagate
MRF energies throughout the frames via bilateral filters without using any
global texture, color or shape model. Recently presented bi-exponential filter
is utilized for efficiency, whereas a novel technique is also developed to
dynamically solve graph-cuts for varying, non-lattice graphs in general linear
filtering scenario. These improvements are experimented for both automatic and
interactive video segmentation scenarios. Moreover, in addition to the
efficiency, segmentation quality is also tested both quantitatively and
qualitatively. Indeed, for some challenging examples, significant time
efficiency is observed without loss of segmentation quality.Comment: Multimedia, IEEE Transactions on (Volume:16, Issue: 5, Aug. 2014
Analytical solutions of the Klein-Fock-Gordon equation with the Manning-Rosen potential plus a Ring-Shaped like potential
In this work, on the condition that scalar potential is equal to vector
potential, the bound state solutions of the Klein-Fock-Gordon equation of the
Manning-Rosen plus ring-shaped like potential are obtained by Nikiforov-Uvarov
method. The energy levels are worked out and the corresponding normalized
eigenfunctions are obtained in terms of orthogonal polynomials for arbitrary
states. The conclusion also contain central Manning-Rosen, central and
non-central Hulth\'en potential.Comment: 14 pages. arXiv admin note: substantial text overlap with
arXiv:1210.537
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