双电机消隙直流驱动器在舰载测量雷达中应用

介绍了在某舰载测量雷达伺服系统改造中,采用双电机消隙直流驱动器构成的伺服系统设计方案及其应用情况。通过直流PWM技术与电消隙、和速反馈等多电机驱动技术的应用,有效克服了摩擦、齿隙、差速振荡等因素的影响。满足了雷达伺服系统大功率、高性能要求。     

基于视觉信息融合的驾驶员疲劳监测方法综述

驾驶疲劳已成为引发交通事故的主要原因,现介绍了疲劳产生的原因以及国内外对于疲劳状态监测技术的研究现状.详细分析了基于视觉信息的五种监测技术,认为没有一种单独的方法能够准确可靠地测量驾驶疲劳,提出了一种基于视觉信息融合的监测方法.     

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.     

Depth video spatial and temporal correlation enhancement algorithm based on just noticeable rendering distortion model

Spatial and temporal inconsistency of depth video deteriorates encoding efficiency in three dimensional video systems. A depth video processing algorithm based on human perception is presented. Firstly, a just noticeable rendering distortion (JNRD) model is formulated by combining the analyses of the influence of depth distortion on virtual view rendering with human visual perception characteristics. Then, depth video is processed based on the JNRD model from two aspects, spatial and temporal correlation enhancement. During the process of spatial correlation enhancement, depth video is segmented into edge, foreground, and background regions, and smoothened by Gaussian and mean filters. The operations of the temporal correlation enhancement include temporal–spatial transpose (TST), temporal smoothing filter and inverse TST. Finally, encoding and virtual view rendering experiments are conducted to evaluate the proposed algorithm. Experimental results show that the proposed algorithm can greatly reduce the bit rate while it maintains the quality of virtual view.     

A depth perception and visual comfort guided computational model for stereoscopic 3D visual saliency

With the emerging development of three-dimensional (3D) related technologies, 3D visual saliency modeling is becoming particularly important and challenging. This paper presents a new depth perception and visual comfort guided saliency computational model for stereoscopic 3D images. The prominent advantage of the proposed model is that we incorporate the influence of depth perception and visual comfort on 3D visual saliency computation. The proposed saliency model is composed of three components: 2D image saliency, depth saliency and visual comfort based saliency. In the model, color saliency, texture saliency and spatial compactness are computed respectively and fused to derive 2D image saliency. Global disparity contrast is considered to compute depth saliency. Particularly, we train a visual comfort prediction function to distinguish stereoscopic image pair as high comfortable stereo viewing (HCSV) or low comfortable stereo viewing (LCSV), and devise different computational rules to generate a visual comfort based saliency map. The final 3D saliency map is obtained by using a linear combination and enhanced by a “saliency-center bias” model. Experimental results show that the proposed 3D saliency model outperforms the state-of-the-art models on predicting human eye fixations and visual comfort assessment.     

Distinguishing and quantification of the human visual pathways using high-spatial-resolution diffusion tensor tractography

Quantification of the living human visual system using MRI methods has been challenging, but several applications demand a reliable and time-efficient data acquisition protocol. In this study, we demonstrate the utility of high-spatial-resolution diffusion tensor fiber tractography (DTT) in reconstructing and quantifying the human visual pathways. Five healthy males, age range 24–37 years, were studied after approval of the institutional review board (IRB) at The University of Texas Health Science Center at Houston. We acquired diffusion tensor imaging (DTI) data with 1-mm slice thickness on a 3.0-Tesla clinical MRI scanner and analyzed the data using DTT with the fiber assignment by continuous tractography (FACT) algorithm. By utilizing the high-spatial-resolution DTI protocol with FACT algorithm, we were able to reconstruct and quantify bilateral optic pathways including the optic chiasm, optic tract, optic radiations free of contamination from neighboring white matter tracts.     

基于OpenGL的交互式全景视频显示系统

随着虚拟现实和多媒体通信技术的快速发展,全景视频作为一种新兴的数字媒体,凭借其良好的临场感和沉浸感在影视娱乐、教育教学、工业仿真、医学研究等众多领域取得广泛应用。为了更好地开展全景视频的相关研究,建立交互式的全景视频显示系统成为了优化和完善全景视频业务的重要前提。本文基于OpenGL渲染技术,结合用户对于全景视频交互操作的需求,搭建了交互式全景视频显示系统,并在该系统上通过实验分析了本系统的交互时延和视频分辨率、帧率的关系。实验结果表明,交互产生的时延和视频分辨率、帧率的大小呈正相关关系。在本平台的设置下,交互产生的时延不超过0.02s,为用户提供了良好的交互性和视觉体验,为全景视频的相关研究与应用开发提供了稳定的平台。     

基于人眼检测优化的立体人机交互技术的研究

随着3D显示技术的逐渐成熟,越来越多基于3D显示技术的产品被应用于各个领域,例如3D电影、裸眼3D电视、体感交互式系统和影像教学等。基于3D显示的人机交互系统也是近年来越来越热门的研究方向,但是却没有高效地利用深度信息作为交互的线索,因此本文提出将3D显示与体感交互结合,实现立体人机交互的虚拟键盘,让用户只需点击屏幕前方键盘的图像即可进行对应按键信息的录入和编辑,其帧率可达10.6fps。针对3D显示中用户视角偏离会导致按键的像在视觉上的偏移,容易造成误输入的问题,在系统中整合人眼检测功能,修正因视角偏离带来按键定位误差,从而实现了准确率100%的字符输入交互功能。