基于Argus图像的舟山东沙海滩对连续风暴的响应研究

海滩对风暴的响应是一个复杂的过程,尤其在连续风暴发生时。本研究利用Argus视频监测系统拍摄的连续图像,从海滩地貌、剖面、海滩滨线、海滩宽度等方面,定量分析了舟山东沙海滩对连续风暴"马勒卡"和"暹芭"的响应特征,并初步探讨了影响海滩地形地貌变化对连续风暴响应的因素。结果表明:(1)风暴"马勒卡"发生后海滩单宽体积变化量平均值为?73.75m3/m,风暴"暹芭"发生后海滩单宽体积变化量的平均值为?54.56m3/m,风暴"马勒卡"使整个海滩滨线平均后退14.75m,风暴"暹芭"使得海滩滨线相对于两次风暴前后退10.91m;(2)在海滩自身因素、外部动力因素以及人类活动等共同作用下海滩对连续风暴产生了复杂的响应。     

一种无人机视频影像快速配准方法

针对应急测绘中对无人机视频数据快速获取及处理的需求,提出了一种无人机视频影像快速配准方法。首先采用时间索引和线性/球面插值方法实现视频帧与无人机定位定姿信息的时间同步,根据数字微分纠正算法实现视频帧的地理编码,实现视频帧间的粗略配准,然后控制仿射变换模型中的缩放因子不变对纠正后视频帧的坐标进行调整,完成视频帧间的精配准:试验结果表明该方法能够得到航带内视频帧较好的配准效果。     

视频测量机器人星识别算法在自动天文定向中的应用

天文定向是通过观测天体确定方位的高精度定向方法,在天文测量中具有重要的作用,实现自动天文定向是目前天文定向的发展趋势。基于视频全站仪的工作模式,本文提出了一种星识别定向方法。首先通过视频测量连续快速拍摄多颗星,再将高度角和方位角差作为匹配条件,识别出各恒星,最后利用观测数据和解算的恒星数据关系获得定向结果,实现天文定向自动化。本文分析了因测站坐标误差和观测误差引起的星识别误差,由此给出匹配阈值,进一步提高了匹配的精确度和准确度。     

改进Yolo-v3的视频图像火焰实时检测算法

为解决现有视频图像火焰检测方法精度低、速度慢的问题,提出了改进Yolo-v3的视频火焰实时检测算法.首先,在特征提取阶段,通过进一步融合多尺度特征提高网络对图像浅层信息的学习能力,以实现小火焰区域的精准识别;其次,在目标检测阶段,利用改进的K-means聚类算法优化多尺度先验框以适应火焰不同尺寸;最后,在改进Yolo-...     

多媒体数字视频监控技术的现状和应用发展

介绍数字化视频监控技术的应用前景,探讨其下一代产品的发展趋势。包括:1)视频压缩算法——决定产品主要特性的技术;2)网络技术——面向未来多用途的视频多媒体设备以及大规模数字视频多媒体网络系统的构成基础;3）智能化技术——数字视频系统根据应用领域的不同可以提供各种智能化的功能。     

Experiments on vision guided docking of an autonomous underwater vehicle using one camera

This paper introduces an underwater docking procedure for the test-bed autonomous underwater vehicle (AUV) platform called ISiMI using one charge-coupled device (CCD) camera. The AUV is optically guided by lights mounted around the entrance of a docking station and a vision system consisting of a CCD camera and a frame grabber in the AUV. This paper presents an image processing procedure to identify the dock by discriminating between light images, and proposes a final approach algorithm based on the vision guidance. A signal processing technique to remove noise on the defused grabbed light images is introduced, and a two-stage final approach for stable docking at the terminal instant is suggested. A vision-guidance controller was designed with conventional PID controllers for the vertical plane and the horizontal plane. Experiments were conducted to demonstrate the effectiveness of the vision-guided docking system of the AUV.     

水下机器人视频图像高效压缩方法研究

水下视频图像压缩一直是有限带宽水声信道实时传输海量视频数据的关键技术之一。本文首先介绍了目前水下机器人和水下视频图像压缩研究存在的主要问题,并综合分析了目前几种高效视频压缩方法的特点并探讨了进一步研究的方向。此外,根据水下视频的成像特点,提出了高效的全局与局部运动混合补偿方案和基于小波变换的预处理方法。初步实验结果表明：本文提出的预处理方法可以有效去除视频图像中存在的大量视觉冗余和空间冗余,提出的混合运动补偿方案可以获得很高的压缩编码效率;但必须进一步研究快速、有效的全局运动估计方法。     

Gauging extreme floods on YouTube: application of LSPIV to home movies for the post‐event determination of stream discharges

Movies taken by witnesses of extreme flood events are increasingly available on video sharing websites. They potentially provide highly valuable information on flow velocities and hydraulic processes that can help improve the post‐flood determination of discharges in streams and flooded areas. We investigated the troubles and potential of applying the now mature large‐scale particle image velocimetry (LSPIV) technique to such flood movies that are recorded under non‐ideal conditions. Processing was performed using user‐friendly, free software only, such as Fudaa‐LSPIV. Typical issues related to the image processing and to the hydrological analysis are illustrated using a selected example of a pulsed flash‐flood flow filmed in a mountainous torrent. Simple corrections for lens distortion (fisheye) and limited incoherent camera movement (shake) were successfully applied, and the related errors were reduced to a few percents. Testing the different image resolution levels offered by YouTube showed that the difference in time‐averaged longitudinal velocity was less than 5% compared with full resolution. A limited number of GRPs, typically 10, is required, but they must be adequately distributed around the area of interest. The indirect determination of the water level is the main source of uncertainty in the results, usually much more than errors because of the longitudinal slope and waviness of the free‐surface of the flow. The image‐based method yielded direct discharge estimates of the base flow between pulses, of the pulse waves, and of the time‐averaged flow over a movie sequence including a series of five pulses. A comparison with traditional indirect determination methods showed that the critical‐depth method may produce significantly biassed results for such a fast, unsteady flow, while the slope‐area method seems to be more robust but would overestimate the time‐averaged flow rate if applied to the high‐water marks of a pulsed flow. Copyright © 2015 John Wiley & Sons, Ltd.     

基于高速公路视频图像的能见度计算

能见度作为重要的气象观测因素之一,影响高速公路行车安全.基于视频资料的能见度计算方法类似于人眼的感知方式,具备对恶劣天气条件和复杂场地的适应性.基于安徽省2016年10月17日、12月1日和7日的3次大雾天气过程,选取跨省分布的3个高速公路站点,使用对应时次下视频图像灰度值均方差与能见度观测值建立计算模型.结果表明：1）随着大雾天气过程变化,模型计算结果较好体现了能见度的变化规律,对高速公路行车具有指导意义;2）基于视频图像的能见度计算方法类似于人眼观测,能见度越高,人眼分辨地物清晰度越高,图像均方差越大;3）由于监测原理和环境差异,能见度测量值与模型计算结果之间存在误差,理论上大雾空间分布越均匀,能见度仪和监控摄像头距离越近,计算误差越低.