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1.
基于扩展卡尔曼滤波的主动视觉跟踪技术   总被引:1,自引:0,他引:1  
提出一种基于主动视觉的物体跟踪系统.该系统利用基于扩展卡尔曼滤波的物体锁定(Object Locked Based on Extended Kalman Filter,OLBEKF)技术,根据物体的运动预测摄像头的运动,并通过控制摄像头的两个关节实现主动跟踪.实际运用表明,在复杂的环境下,能够实时地获得高准确率的跟踪结果,并且显著提高摄像头拍摄图像的质量.  相似文献   

2.
It is important to detect the driver fatigue at early stage in order to prevent accidents caused by tired operation. This paper presents a non-intrusive computer vision system for real-time monitoring driver's fatigue, which is based on active remote infrared (IR) illumination for real time eye tracking. In the system, using the image captured by IR camera, a more efficient method--luminance weight contrasting circle template with distance divisive is developed to detect the bright-pupils accurately in a short time. And a 3D face model with features of eyes and nostrils is constructed helping to predict and track the positions of eyes. The system can be equipped in the panel of a car and work well in most lighting conditions. Some valuable experimental results and some statistic data about the system are shown.  相似文献   

3.
针对应用CamShift算法进行目标跟踪过程中,当目标被严重遮挡、目标被与目标颜色相近的背景干扰时易丢失跟踪目标的问题,提出了一种基于CamShift和Kalman滤波组合的改进跟踪算法;为克服目标因严重遮挡而丢失的缺陷,利用自适应算法改进了传统的CamShift算法,扩大了搜索窗口,使运动目标位于搜索窗口内;为解决目标因颜色相近背景干扰而丢失的问题,改善跟踪准确率,利用卡尔曼滤波预测目标运动空间位置,作为下一帧搜索窗口的质心坐标;基于上述改进,利用C++语言,研发了改进的CamShift目标跟踪软件模块,给出了该模块的算法流程;实验结果表明,改进后的目标跟踪算法能有效地克服传统CamShift算法的缺陷,大大提高运动目标跟踪的准确性;所提的算法可以应用于运动小车跟踪,人脸识别等领域。  相似文献   

4.
基于卡尔曼滤波的移动机器人运动目标跟踪   总被引:4,自引:0,他引:4  
提出了一种基于卡尔曼滤波的运动目标快速跟踪算法。针对复杂背景下彩色运动目标跟踪问题,采用基于颜色特征和形状特征相结合的方法进行目标识别。利用卡尔曼滤波器的预测功能,预测运动目标在下一帧中的位置,将图像全局搜索问题转换为局部搜索,提高了系统的实时性。实验结果表明:该算法满足移动机器人运动控制的实时性要求,实现了对运动目标的快速跟踪。  相似文献   

5.
视频目标跟踪在军事和民用领域有着广泛的应用,其实现算法首选卡尔曼滤波算法,但是在应用卡尔曼滤波算法之前首先要获得目标当前时刻的观测信息,在全帧图像搜索并确定目标需要耗费大量的计算资源,针对这一问题,本文结合目标跟踪时的卡尔曼滤波算法,在每次完成目标状态的滤波估计后,进行卡尔曼一步预测,确定目标下一时刻可能的范围,避免下一时刻确定量测信息时对整幅图像的搜索,极大地减小计算量,提高目标跟踪的实时性和精度。计算机仿真实验验证了本文所提方法的有效性。  相似文献   

6.
基于卡尔曼滤波的交通参数采集系统   总被引:2,自引:0,他引:2  
基于计算机视觉的交通监控系统,已成为交通管理的主要手段,车辆的实时检测和追踪是智能交通监控系统的核心。文中介绍了公安部智能交通项目的交通信号采集模块中使用的关于多物体追踪的一些方法,主要采用了子特征提取方法和kalman滤波统计模型,建立起物体的追踪模型。在其基础上实现目标的检测和追踪,及最终的交通参数的测量。  相似文献   

7.
利用对目标旋转、尺度变化、视角变化等具有稳定性的尺度不变特征变换(SIFT)算法,提出一种适用于基于圆轨的基线可调双目主动视觉监测平台的目标识别方法,通过离线建立物体的多侧面SIFT特征点数据库,将三维空间的目标转换为二维特征描述,利用二维特征描述实现三维空间目标的识别,以提高匹配识别效率。实验结果表明,该方法能实时准确地识别目标。  相似文献   

8.
运动目标跟踪技术是未知环境下移动机器人研究领域的一个重要研究方向。该文提出了一种基于主动视觉和超声信息的移动机器人运动目标跟踪设计方法,利用一台SONY EV-D31彩色摄像机、自主研制的摄像机控制模块、图像采集与处理单元等构建了主动视觉系统。移动机器人采用了基于行为的分布式控制体系结构,利用主动视觉锁定运动目标,通过超声系统感知外部环境信息,能在未知的、动态的、非结构化复杂环境中可靠地跟踪运动目标。实验表明机器人具有较高的鲁棒性,运动目标跟踪系统运行可靠。  相似文献   

9.
Obstacle detection is an essential capability for the safe guidance of autonomous vehicles, especially in urban environments. This paper presents an efficient method to integrate spatial and temporal constraints for detecting and tracking obstacles in urban environments. In order to enhance the reliability of the obstacle detection task, we do not consider the urban roads as rigid planes, but as quasi-planes, whose normal vectors have orientation constraints. Under this flexible road model, we propose a fast, robust stereovision based obstacle detection method. A watershed transformation is employed for obstacle segmentation in dense traffic conditions, even with partial occlusions, in urban environments. Finally a UKF (Unscented Kalman filter) is applied to estimate the obstacles parameters under a nonlinear observation model. To avoid the difficulty of the computation in metric space, the whole detection process is performed in the disparity image. Various experimental results are presented, showing the advantages of this method.Qian Yu received the B.E. degree in Computer Science from Tsinghua University, Beijing, China, in 2001, and the Master degree in Computer Science also from Tsinghua University in 2004, working at the Artificial Intelligence Laboratory. From October 2002 to April 2003, he was a visiting student at the Institute of System and Robotics (ISR), University of Coimbra, Portugal. His current research interests are in computer vision and robotics.Helder Araujo is currently Associate Professor in the Department of Electrical and Computer Engineering, University of Coimbra, Portugal. He is co-founder of the Portuguese Institute for Systems and Robotics (ISR), where he is now a Researcher and Vice-Director of the Coimbra pole. His primary research interests are in computer vision and mobile robotics.Hong Wang received his Ph.D. degree from the Department of Computer Science and Technology, Tsinghua University in 1993. He is currently an associate professor at Department of Computer Science and Technology, Tsinghua University. He worked as a visiting researcher at the Department of Intelligent Assistant Driving, Daimler-Benz Research, Stuttgart, Germany, from August 1996 to August 1997. His main research interests include Artificial Intelligence, Mobile Robotics, Vision Navigation, Multi-sensor Data Fusion. He has published over 40 papers in international conference and journals. He is a member of Special Committee of Machine Perception and Virtual Reality of the Chinese Association of Artificial Intelligence and a member of Scientific Committee of the Olympiad in Informatics of the Chinese Computer Association. He has served as an Associated Director of the Central Laboratory of the State Key Laboratory of Intelligent Technology and Systems, Tsinghua University.  相似文献   

10.
主要研究动态背景下的运动目标检测和跟踪问题。背景补偿差分法是一种常用的动态背景下运动目标检测算法,但检测到的目标轮廓要比其真实轮廓大,检测结果不准确且算法复杂度较高。主动轮廓模型在图像分割和目标提取过程中具有拓扑结构变化灵活性,对数值计算方案的设计更加方便、有效,据此提出一种基于改进C-V模型和卡尔曼滤波的算法,用来检测和跟踪动态背景下的运动目标。提出的算法利用C-V模型曲线演化检测和跟踪目标,使C-V模型在目标的边缘处收敛。结合卡尔曼滤波预测运动目标下一帧位置,从而实现对运动目标轮廓的跟踪。实验结果表明,该方法可以对动态背景下运动目标进行精确的检测与跟踪。  相似文献   

11.
基于活动基模型的非刚体目标跟踪算法研究   总被引:1,自引:1,他引:0       下载免费PDF全文
近年来,非刚体目标跟踪技术作为视频目标跟踪中的一个难点受到了广泛关注。为了精确跟踪非刚体目标,克服跟踪过程中目标形状变化和遮挡带来的困难,提出一种基于活动基模型的非刚体目标跟踪算法。首先采用共享草图算法从目标训练样本集中学习得到目标的活动基模型,然后把活动基模型嵌入粒子滤波观测模型中。在对金鱼与企鹅序列跟踪的实验结果表明,与现有算法相比,该算法在非刚体目标形状变化以及存在遮挡的情况下,具有更好的跟踪性能。  相似文献   

12.
为实现对海上运动目标的实时跟踪,克服跟踪效果易受到严重遮挡影响的缺点,建立了一套实时跟踪系统,并且结合目标的运动信息与新的模型更新策略,对均值漂移与卡尔曼滤波器相结合的跟踪算法做出了改进.当运动船只被遮挡的比例较大时,先用估计出的目标速度矢量更新卡尔曼滤波器,并用相应的模型更新策略更新目标模型以提高模型相似性度量的精确性,再单独利用滤波器进行跟踪,取得了较好的跟踪效果.实验结果表明,该系统可以较好地实现海上运动目标的跟踪,并且改进后的算法具有良好的实时性和鲁棒性.  相似文献   

13.
邱雪娜  刘士荣 《机器人》2011,33(2):181-190
为了提高复杂环境下的目标跟踪精度,提出了一种基于序贯检测机制的双目视觉运动目标跟踪方法.该方法在序贯检测机制下,将粒子滤波、稀疏场主动轮廓和CamShift等方法结合.首先用基于颜色特征的粒子滤波估计最优跟踪窗口;通过跟踪窗口和目标的相似度决定足否采用稀疏场主动轮廓方法,然后由目标轮廓和目标的相似度决定是否需要CamS...  相似文献   

14.
This paper describes an application of computer vision techniques to road surveillance. It reports on a project undertaken in collaboration with the Research and Innovation group at the Ordnance Survey. The project aims to produce a system that detects and tracks vehicles in real traffic scenes to generate meaningful parameters for use in traffic management. The system has now been implemented using two different approaches: a feature-based approach that detects and groups corner features in a scene into potential vehicle objects, and an appearance-based approach that trains a cascade of classifiers to learn the appearances of vehicles as an arrangement of a set of pre-defined simple Haar features. Potential vehicles detected are then tracked through an image sequence, using the Kalman filter motion tracker. Experimental results of the algorithms are presented in this paper.  相似文献   

15.
跟踪遮挡目标的一种鲁棒算法   总被引:2,自引:0,他引:2  
为了解决在跟踪目标过程中的遮挡问题,引入Kalman滤波器为Mean Shift跟踪算法选择初始点,在跟踪稳定的情况下进行模型更新以消除由于目标缓慢变化而产生的累积误差对跟踪结果的影响。根据Kalman滤波器残差的大小判定是否发生遮挡,遮拦检测算法对目标进行分块检测从而把遮挡分为部分遮挡和完全遮挡两种情况,并对两种情况进行区别讨论:对部分遮挡情况不做特殊处理;对完全遮挡情况,结合目标的运动方向提出6点搜索策略来找回目标。实验表明,该算法能很好地解决跟踪运动目标过程中目标的遮挡问题。  相似文献   

16.
提出一种基于模糊逻辑的主/被动雷达传感器数据融合算法。首先将单个雷达的测量值通过时间校准后,将它们作为卡尔曼滤波器的输入分别滤波,然后再对滤波后的目标状态估计进行融合。融合算法基于卡尔曼滤波的协方差匹配关系,采用模糊推理得到数据融合的权值。最后将各传感器的卡尔曼滤波状态估计进行加权融合得到所需要的目标状态信息。采用该融合算法可以有效提高目标跟踪系统的抗干扰能力。仿真结果表明该算法有效。  相似文献   

17.
提出一种机器人捕捉运动目标的动力学视觉伺服方法。基于位置阻抗控制器,通过双目立体视觉检测并跟踪运动目标的位置,结合CMAC网络,采用以视觉阻抗的二次型为训练目标的学习型视觉阻抗控制器,用于克服控制器对系统结构参数变化适应性差的缺点,并对阻抗参数进行优化。实验结果表明,该视觉伺服方法在机器人捕捉运动目标时具有良好的动力学特性和轨迹控制效果。  相似文献   

18.
一种新的混合有源滤波器控制方法   总被引:1,自引:0,他引:1  
针对混合有源滤波器HAPF的传统控制方法中存在的不足,提出了一种基于离散滑模控制算法的电流跟踪控制方法,避免了传统控制原理中系统滤波能力与稳定性之间的矛盾,不仅系统响应迅速,而且具有满意的控制精度,易于实现数字控制,仿真结果说明新的控制方法是行之有效的。  相似文献   

19.
This paper presents a novel viewpoint selection criterion for active object recognition and pose estimation whose key advantage resides in its low computational cost with respect to current popular approaches in the literature. The proposed observation selection criterion associates high utility with observations that predictably facilitate distinction between pairs of competing hypotheses by a Bayesian classifier. Rigorous experimentation of the proposed approach was conducted on two case studies, involving synthetic and real data, respectively. The results show the proposed algorithm to perform better than a random navigation strategy in terms of the amount of data required for recognition while being much faster than a strategy based on mutual information, without compromising accuracy.  相似文献   

20.
夏轩  刘华平  许伟明  孙富春 《机器人》2012,34(3):354-362
为了提高目标检测的快速性与准确性,简化基于粒子滤波的目标跟踪算法中的直方图计算,提高检测和跟踪算法在基于DSP(数字信号处理器)的主动视觉系统上的运行速度,提出了一种基于DSP的机器人主动视觉系统.该系统通过改进的EMCV(embedded computer vision library)与启发式搜索方法,在DSP上实现了AdaBoost检测算法;利用增量式直方图计算算法实现粒子滤波中颜色直方图与边缘方向直方图的计算,将直方图融合到观测模型中,在DSP上实现并优化了目标跟踪算法.实验证实了该主动视觉系统中算法的快速性与系统的鲁棒性.  相似文献   

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