On Relativistic Generalization of Gravitational Force

In relativistic theories, the assumption of proper mass constancy generally holds. We study gravitational relativistic mechanics of point particle in the novel approach of proper mass varying under Minkowski force action. The motivation and objective of this work are twofold: first, to show how the gravitational force can be included in the Special Relativity Mechanics framework, and, second, to investigate possible consequences of the revision of conventional proper mass concept (in particular, to clarify a proper mass role in the divergence problem). It is shown that photon motion in the gravitational field can be treated in terms of massless refracting medium, what makes the gravity phenomenon compatible with SR Mechanics framework in the variable proper mass approach. Specifically, the problem of point particle in the spherical symmetric stationary gravitational field is studied in SR-based Mechanics, and equations of motion in the Lorentz covariant form are obtained in the relativistic Lagrangean problem formulation. The dependence of proper mass on potential field strength is derived from the Euler-Lagrange equations as well. One of new results is the elimination of conventional 1/r divergence, which is known to be not removable in Schwarzschild gravitomechanics. Predictions of particle and photon gravitational properties are in agreement with GR classical tests under weak-field conditions; however, deviations rise with potential field strength. The conclusion is made that the approach of field-dependent proper mass is perspective for development of SR gravitational mechanics and further studies of gravitational problems.     

Automatic correction of in-plane bulk motion artifacts in self-navigated radial MRI

Radial MRI is typically used for scans that are sensitive to unavoidable motion. While the translational motion artifact can be easily removed from the radial trajectory data by phase correction, correction of rotational motion still remains a challenge in radial MRI. We present a novel method to refocus the image corrupted by view-to-view motion in the view-interleaved radial MRI data. In this method, the error in rotational view angles was modeled as a polynomial function of the view order and the model parameters were estimated by minimizing the self-navigator image metrics such as image entropy, gradient entropy, normalized gradient squared and mean square difference. Translational motion correction was conducted by aligning the projection profiles. Simulation studies were conducted to demonstrate the robustness of both translational and rotational motion correction methods in different noise levels. The proposed method was successfully applied to correct for motion of healthy subjects. Substantial motion correction with relative error of less than 5% was achieved by using either first- or second-order model with the image metrics. This study demonstrates the potential of the method for motion-sensitive applications.     

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in echo-planar imaging

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is "corrected" with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.     

高能X射线工业CT扫描运动控制系统设计

 分析了高能X射线工业CT扫描运动控制系统的作用,提出了扫描运动控制系统的组成方案。控制系统由工业控制计算机、计数卡、控制卡、伺服驱动器、伺服电机、工作平台、光栅和控制软件组成。研究了在Windows驱动程序模式（WDM）下,控制系统设备驱动程序的组成。以运动控制卡为例,研究了开发控制系统设备驱动程序的方法,并分析了设备驱动程序和用户程序交互的过程。通过编写WDM驱动程序,实现了对高能X射线工业CT扫描运动系统的实时控制。实验结果表明,开发的扫描运动控制系统,可靠性和实时性满足要求。     

Robust optical flow estimation via edge preserving filtering

It is known that optical flow estimation techniques suffer from the issues of ill-defined edges and boundaries of the moving objects. Traditional variational methods for optical flow estimation are not robust to handle these issues since the local filters in these methods do not hold the robustness near the edges. In this paper, we propose a non-local total variation NLTV-$L^1$ optical flow estimation method based on robust weighted guided filtering. Specifically, first, the robust weighted guided filtering objective function is proposed to preserve motion edges. The proposed objective function is based on the linear model which is computationally efficient and edge-preserving in complex natural scenarios. Second, the proposed weighted guided filtering objective function is incorporated into the non-local total variation NLTV-$L^1$ energy function. Finally, the novel NLTV-$L^1$ optical flow method is performed using the coarse-to-fine process. Additionally, we modify some state-of-the-art variational optical flow estimation methods by the robust weighted guided filtering objective function to verify the performance on Middlebury, MPI-Sintel, and Foggy Zurich sequences. Experimental results show that the proposed method can preserve edges and improve the accuracy of optical flow estimation compared with several state-of-the-art methods.     

基于线状特性的大数据地铁用户识别与定位方法

从MR原始数据特性出发研究数据结构与字段,采用基于线状特性分析MR大数据的地铁用户识别过滤方法和位置定位方法,该方法经过验证能够有效输出地铁用户数据并定位在地图上,解决人工地铁测试效率低且测试片面的问题,实现基于大数据的自动化地铁网络评估,提供海量的有效定位数据用于地铁评估与分析。     

Content adaptive video denoising based on human visual perception

In this paper, we propose content adaptive denoising in highly corrupted videos based on human visual perception. We introduce the human visual perception in video denoising to achieve good performance. In general, smooth regions corrupted by noise are much more annoying to human observers than complex regions. Moreover, human eyes are more interested in complex regions with image details and more sensitive to luminance than chrominance. Based on the human visual perception, we perform perceptual video denoising to effectively preserve image details and remove annoying noise. To successfully remove noise and recover the image details, we extend nonlocal mean filtering to the spatiotemporal domain. With the guidance of content adaptive segmentation and motion detection, we conduct content adaptive filtering in the YUV color space to consider context in images and obtain perceptually pleasant results. Extensive experiments on various video sequences demonstrate that the proposed method reconstructs natural-looking results even in highly corrupted images and achieves good performance in terms of both visual quality and quantitative measures.     

Robust visual tracking via CAMShift and structural local sparse appearance model

This paper addresses issues in visual tracking where videos contain object intersections, pose changes, occlusions, illumination changes, motion blur, and similar color distributed background. We apply the structural local sparse representation method to analyze the background region around the target. After that, we reduce the probability of prominent features in the background and add new information to the target model. In addition, a weighted search method is proposed to search the best candidate target region. To a certain extent, the weighted search method solves the local optimization problem. The proposed scheme, designed to track single human through complex scenarios from videos, has been tested on some video sequences. Several existing tracking methods are applied to the same videos and the corresponding results are compared. Experimental results show that the proposed tracking scheme demonstrates a very promising performance in terms of robustness to occlusions, appearance changes, and similar color distributed background.     

面向“金课”建设需求的“运动控制”教学研究

为提升教学质量,紧跟科学技术发展的前沿,响应“金课”建设的需求,本文从运动控制课程中现有控制技术出发,以五相内嵌式永磁同步电机控制为例,通过离散化电机模型,设计一种具有前沿性的电机控制策略,并通过仿真和实验验证该理论的可实施性。该教学研究不仅对运动控制课程中传统的矢量控制和直接转矩控制进行了有力补充,同时提升了课程的前沿性和挑战度,对于打造“金课”建设具有重要实践意义。     

基于Leap Motion手语语音转换的设计与实现

文章介绍了基于Leap Motion手语语音转换的原理以及在实际中如何实现应用,其能够将手语手势翻译成所需语言,并且以语音的形式传递消息,实现为聋哑人"发声"的目的。Leap Motion手语语音转换的硬件部分采用Leap Motion体感控制器,能够实时采集人手指的坐标、加速度、方向等动态手势的运动信息。软件采用Unity 3D三维引擎,提供了开发手势识别的SDK,并给出了一些基本手的模型,在Unity 3D中完成由手势到文字,再到语音的转换。