Hand gesture pointing location detection

Gesture recognition has been implemented in many systems for different purposes. The way it is used can be different from system to system. Few used them as touch objects using sensors while few use them as pointing object where the camera is in front of the hand, but the location is being pointed by human, can be detected only if the camera is behind that person. This paper presents an automatic system to detect the location on the wall where the user is currently pointing by his hand. This is done with the detection of head and both hands. The shoulders and elbows’ locations are identified using geometry analysis to understand the current gesture of the human and finally the direction where user hand is pointing would be detected. The face was detected using Haar classifier and shoulders were estimated using the rectangle method near the head. This method does not work in poor illumination conditions and is made to detect only one person at a time. Also user is supposed to wear half sleeve or sleeveless shirt for the better segmentation.     

基于LAMOST光谱的恒星大气物理参数估计

基于实测光谱的恒星大气物理参数估计是探索恒星本质的首要任务。随着郭守敬望远镜(LAMOST)进入正式巡天阶段,正以前所未有的速度获取海量的恒星实测光谱数据,这为星系研究带来了新的机遇和挑战。由于LAMOST是多目标光纤光谱天文望远镜,获取的光谱噪音比较大。光谱前期处理中的波长定标和流量定标精度不高,导致光谱存在微小畸变,这些都大大增加了恒星大气物理参数测量的难度。如何对LAMOST实测光谱的恒星大气物理参数进行自动测量是迫切期待需要研究的一个重要课题,关键是如何消除噪声,提高恒星大气物理参数的测量精度和鲁棒性。提出了一个测量LAMOST恒星光谱大气参数的回归模型(SVM(lasso))。基本思路是:首先使用Haar小波对光谱信号进行滤波,抑制光谱中噪声的不利影响,最大限度地保留光谱判别信息。然后采用lasso算法进行特征选择,选取与恒星大气物理参数相关性强的特征。最后将选择的光谱特征输入支持向量机回归模型对恒星大气物理参数进行估计,该模型对光谱畸变和噪音的容忍性比较好,提高了测量的精确度。为了验证上述方案的可行性,在33 963条LAMOST先导巡天恒星光谱库上作了实验研究,三个恒星大气物理参数的精度分别为log Teff:0.006 8dex,log g:0.1551dex,[Fe/H]:0.104 0dex。     

Exponential mixing for dissipative PDEs with bounded non-degenerate noise

We prove that well posed quasilinear equations of parabolic type, perturbed by bounded nondegenerate random forces, are exponentially mixing for a large class of random forces.     

Haar小波求解非线性分数阶偏微分方程

考虑一类时间-分数阶偏微分方程,将Haar小波与算子矩阵思想有效结合,对已知函数进行恰当的离散,将时间-分数阶偏微分方程转化为矩阵方程,使得计算更简便,并给出数值算例验证了方法的有效性.     

小波分析在视频检测中的应用

针对复杂背景下机器视觉系统中运动目标的检测,提出一种基于小波分析的运动目标检测方法。首先,利用双Haar小波软阈值法,去除视频图像的噪声。然后,建立了一种基于小波变换的运动目标检测算法,直接在二进小波变换域提取运动区域,从而检测出运动目标。实验结果表明,本文方法可以有效地从图像序列中检测出完整的运动目标,而且在平滑噪声的同时还可以保护图像边缘细节不受损失,效果要好于传统帧差法。     

Numerical solution of nonlinear Fredholm integral equations of the second kind using Haar wavelets

In this work, we present a computational method for solving nonlinear Fredholm integral equations of the second kind which is based on the use of Haar wavelets. Error analysis is worked out that shows efficiency of the method. Finally, we also give some numerical examples.     

Boundaries of compact convex sets and fragmentability

If X is a compact convex set in a real locally convex space, B⊂X is said to be its boundary if every affine continuous function on X attains its maximum at some point of B. We study relations between fragmentability of B and the whole set X. As a byproduct we obtain a characterization of separable Asplund spaces. We also study the possibility of finding the Haar system in a boundary of a metrizable compact convex set.     

A wavelet method for solving singular integral equation of MHD

This paper presents Haar wavelet approximation to solve a singular integral equation which has singularities on a diagonal of the domain R=[-1,1]×[-1,1]. The singularities arise basically due to modified Bessel function K₀ which appears as a part of the kernel. Thus the integral equation is weakly (logarithmically) singular only. The problem is solved considering all the singularities of the kernel and results are examined for approximations of different orders. Our interest to solve the problem using Haar wavelet basis is due to its simplicity and efficiency in numerical approximation. The results show convergence trend as mesh is refined. Comparison is made with some available results obtained earlier by partial consideration of the singularities.     

Solving fractional integral equations by the Haar wavelet method

Haar wavelets for the solution of fractional integral equations are applied. Fractional Volterra and Fredholm integral equations are considered. The proposed method also is used for analysing fractional harmonic vibrations. The efficiency of the method is demonstrated by three numerical examples.