2,216 research outputs found
AN ADAPTIVE BACKGROUND UPDATION AND GRADIENT BASED SHADOW REMOVAL METHOD
Moving object segmentation has its own niche as an important topic in computer vision. It has avidly being pursued by researchers. Background subtraction method is generally used for segmenting moving objects. This method may also classify shadows as part of detected moving objects. Therefore, shadow detection and removal is an important step employed after moving object segmentation. However, these methods are adversely affected by changing environmental conditions. They are vulnerable to sudden illumination changes, and shadowing effects. Therefore, in this work we propose a faster, efficient and adaptive background subtraction method, which periodically updates the background frame and gives better results, and a shadow elimination method which removes shadows from the segmented objects with good discriminative power. Keywords- Moving object segmentation
Sub-convexity bound for -functions: -spectral aspect
Let be a Hecke-Maass cusp form for with Langlands
parameters satisfying
with . Let be a holomorphic or Maass
Hecke eigenform for . In this article, we prove a
sub-convexity bound for the central values
of the Rankin-Selberg -function of and , where the implied
constants may depend on and .
Conditionally, we also obtain a subconvexity bound for when the spectral parameters of are in generic position,
that is
Comment: First draf
Hybrid subconvexity bound for -functions: t and level aspect
\begin{abstract}
In this article, we will get non-trivial estimates for the central values of
degree six Rankin-Selberg -functions associated
with a form and a form using the delta symbol
approach in the hybrid settings i.e. in the level of form and
-aspect.
\end{abstract}Comment: 30 pages, comments are welcom
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