Motion editing requires the preservation of spatial and temporal information of the motion. During editing, this information should be preserved at best. We propose a new representation of the motion based on the Laplacian expression of a 3D+t graph: the set of connected graphs given by the skeleton over time. Through this Laplacian representation of the motion, we propose an application which ...

This paper presents a Laplacian-based image filtering method. Using a local noise estimator function in an energy functional minimizing scheme we show that Laplacian that has been known as an edge detection function can be used for noise removal applications. The algorithm can be implemented on a 3x3 window and easily tuned by number of iterations. Image denoising is simplified to the reduction...

The alleged high net energy cost of running and low net energy cost of walking in humans have played an important role in the interpretation of the evolution of human bipedalism and the biomechanical determinants of the metabolic cost of locomotion. This study re-explores how the net metabolic energy cost of running and walking (J kg(-1) m(-1)) in humans compares to that of animals of similar m...

let $g = (v, e)$ be a simple graph. denote by $d(g)$ the diagonal matrix $diag(d_1,cdots,d_n)$, where $d_i$ is the degree of vertex $i$  and  $a(g)$ the adjacency matrix of $g$. the  signless laplacianmatrix of $g$ is $q(g) = d(g) + a(g)$ and the $k-$th signless laplacian spectral moment of  graph $g$ is defined as $t_k(g)=sum_{i=1}^{n}q_i^{k}$, $kgeqslant 0$, where $q_1$,$q_2$, $cdots$, $q_n$ ...

U-Net++ is one of the most prominent deep convolutional neural networks in field medical image segmentation after U-Net. However, semantic gaps between encoder and decoder subnets are still large, which will lead to fuzzy feature maps even target regions segmentation. To solve this problem, we propose an improved model utilizing channel attention mechanism Laplacian sharpening filter, SCU-Net++...

‎For a simple graph $G$‎, ‎the signless Laplacian Estrada index is defined as $SLEE(G)=sum^{n}_{i=1}e^{q^{}_i}$‎, ‎where $q^{}_1‎, ‎q^{}_2‎, ‎dots‎, ‎q^{}_n$ are the eigenvalues of the signless Laplacian matrix of $G$‎. ‎In this paper‎, ‎we first characterize the unicyclic graphs with the first two largest and smallest $SLEE$'s and then determine the unique unicyclic graph with maximum $SLEE$ a...

The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced using considering the focus measurement in the spatial domain. However, the multi-focus image ...