基于FPGA的动态目标跟踪系统设计

为了解决基于PC机的视频动态目标跟踪实时性瓶颈问题,设计出一种基于FPGA的动态目标跟踪系统。设计遵循图像处理金字塔模型,针对低层和中层算法简单、数据量大且存在一定并行性等特点采用FPGA硬件实现,而高层较复杂算法使用Nios Ⅱ软核进行C语言编程。整个设计采用Verilog-HDL对算法完成建模与实现,并在QUARTUS Ⅱ上进行了综合、布线等工作,最后以Altera公司的DE2开发板为硬件平台实现了整个系统。     

相似背景下的运动目标自动跟综问题研究

研究视频图像中准确实现运动目标跟踪问题,要求在视频图像中找到目标确切位置,并反馈给跟踪系统.针对传统基于特征匹配的跟踪,当被跟踪物体所处环境中存在颜色、形状接近的物体时,会出现像素特征误匹配,造成运动目标跟踪错误率较高.提出基于Markov Chain Monte Carlo数据关联的运动目标跟综方法.通过建立像素概率模型,将运动日标跟踪问题公式化,运用MCMC方法对后验概率进行采样估计,避免了,模型匹配像素点的不确定性.实验证明,运动目标跟踪方法实现了在与自身相似背景下的准确跟踪,有效降低了跟踪错误率,取得了满意的效果.     

Moving object detection using region tracking

For many vision-based systems, it is important to detect a moving object automatically. The region-based motion estimation method is popular for automatic moving object detection. The region-based method has several advantages in that it is robust to noise and variations in illumination. However, there is a critical problem in that there exists an occlusion problem which is caused by the movement of the object. The occlusion problem results in an incorrect motion estimation and faulty detection of moving objects. When there are occlusion regions, the motion vector is not correctly estimated. That is, a stationary background in the occluded region can be classified as a moving object.In order to overcome this occlusion problem, a new occlusion detection algorithm is proposed. The proposed occlusion detection algorithm is motivated by the assumption that the distribution of the error histogram of the occlusion region is different from that of the nonocclusion region. The proposed algorithm uses the mean and variance values to decide whether an occlusion has occurred in the region. Therefore, the proposed occlusion detection and motion estimation scheme detects the moving regions and estimates the new motion vector, while avoiding misdetection caused by the occlusion problem. The experimental results for several video sequences demonstrate the robustness of the proposed approach to the occlusion problem.This work was presented in part at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

双边界限定下的运动目标跟踪方法

针对目标跟踪领域中复杂背景下的目标提取、目标与目标以及目标与背景之间的相互遮挡、阴影的处理、目标跟踪的实时性及鲁棒性等问题,提出一种双边界限定下的运动目标跟踪算法。利用金字塔光流法对目标关键点进行长时间无模型跟踪,并将其与检测到的前景关键点进行不重复地融合。根据融合得到的关键点,评估尺度因子及旋转因子,并利用全部前景关键点对目标中心点进行概率性表决。再利用双边界限定方法使边界上关键点对目标进行可靠描述,提升系统的鲁棒性。     

基于Mean Shift和粒子滤波的运动目标跟踪

针对Mean Shift算法跟踪效果不佳以及粒子滤波算法计算量大且实时性不强等问题,提出了一种结合Mean Shift和粒子滤波的运动目标跟踪融合算法。首先用MeanShift算法进行跟踪,在跟踪结果不佳的情况下用粒子滤波算法进行修正。实验结果表明,融合算法很好地结合了两种算法的优点,既保留了Mean Shift算法的实时性,又很好地体现了粒子滤波算法的鲁棒性,实用性很强。     

Narrowband target tracking using a biomimetic sonarhead

This work presents a target tracking method that exploits both the physics of narrowband echolocation and appropriate movements of the sensor, taking inspiration from narrowband (CF-FM) bats. The platform used in this work is RoBat, a biomimetic sonarhead mounted on a mobile platform. Two different techniques are integrated in the tracker. First, Barshan’s and Kuc’s method for estimating target range and azimuth angle is adapted to the geometry of the sonarhead. Next, Walker’s arc scanning hypothesis for target elevation estimation in CF-FM bats is implemented, applying curve fitting for an accurate estimation of the peak-delay. The integration of both techniques in a preliminary 3D tracking system is performed applying both methods independently.     

逐次分块差分直方图对运动目标的提取

为从视频图像序列中准确且完整地提取运动目标,提出一种基于运动差分直方图的目标提取算法。通过对视频图像序列中两帧相邻图像以及它们的差分图像进行逐次分块,分析对应分块的差分直方图,利用背景区域块与目标区域块对应的差分直方图分布不同,逐步去除背景提取目标,有效避免提取的目标内部出现空洞,以块为单位的处理提高算法运行速度。通过数值实验验证了该算法具有较好检测性。     

Bearings only single-sensor target tracking using Gaussian mixtures

This paper presents a new approach for single sensor tracking using passive bearings only measurements. Gaussian mixture measurement presentation, together with a track splitting algorithm, allow space-time integration of the target position uncertainty with a simple algorithm. The bearings-only measurements are incorporated into track as they arrive using a dynamic bank of linear Kalman filters. While this approach is applicable to the case with the target detection, data association and multitarget issues, this paper concentrates on the target trajectory estimation using associated measurements. A simulation study demonstrates the benefits of this approach.     

均值漂移框架下基于背景差分的运动目标跟踪

提出了一种基于背景差分法原理的均值漂移MS跟踪算法。使用距离度量函数判断目标是否失去跟踪,当MS跟踪目标位置发生较大偏移时,通过使用背景差分法提取的目标形心位置对其进行修正。实验结果表明,该方法应用于实时运动目标的跟踪时具有良好的跟踪效果。     

Joint spatial registration and multi-target tracking using an extended PM-CPHD filter

An extended product multi-sensor cardinalized probability hypothesis density (PM-CPHD) filter for spatial registration and multi-target tracking (MTT) is proposed. The number and states of targets and the biases of sensors are jointly estimated by this method without the data association. Monte Carlo (MC) simulation results show that the proposed method (i) outperforms, although computationally more expensive than, the extended multi-sensor PHD filter which has been proposed for joint spatial registration and MTT; (ii) outperforms the multi-sensor joint probabilistic data association (MSJPDA) filter which is also extended in this study for joint spatial registration and MTT when the clutter is relatively dense.     

Nonlinear filtering in target tracking using cooperative mobile sensors

Collaborative signal processing and sensor deployment have been among the most important research tasks in target tracking using networked sensors. In this paper, the mathematical model is formulated for single target tracking using mobile nonlinear scalar range sensors. Then a sensor deployment strategy is proposed for the mobile sensors and a nonlinear convergent filter is built to estimate the trajectory of the target.     

基于差分法的均值漂移单目标跟踪

研究了一种基于差分法原理的MS跟踪算法。当MS跟踪目标位置发生较大偏移时,通过使用差分法提取的目标形心位置对其进行修正。实验结果表明,该方法应用于运动目标的跟踪具有良好的跟踪效果。     

目标跟踪状态估计排序粒子群算法研究

基于视觉的无人机地面目标跟踪状态估计为非线性滤波问题,针对使用一般粒子滤波算法存在粒子退化和计算量大的缺陷问题,提出了一种基于排序的粒子滤波算法,对粒子依误差大小进行排序并计算粒子权重。仿真试验表明,该方法减轻了粒子贫化的影响,提高了状态估计精度。     

Chance-constrained target tracking using sensors with bounded fan-shaped sensing regions

We present a robust target tracking algorithm for a mobile robot. It is assumed that a mobile robot carries a sensor with a fan-shaped field of view and finite sensing range. The goal of the proposed tracking algorithm is to minimize the probability of losing a target. If the distribution of the next position of a moving target is available as a Gaussian distribution from a motion prediction algorithm, the proposed algorithm can guarantee the tracking success probability. In addition, the proposed method minimizes the moving distance of the mobile robot based on the chosen bound on the tracking success probability. While the considered problem is a non-convex optimization problem, we derive a closed-form solution when the heading is fixed and develop a real-time algorithm for solving the considered target tracking problem. We also present a robust target tracking algorithm for aerial robots in 3D. The performance of the proposed method is evaluated extensively in simulation. The proposed algorithm has been successful applied in field experiments using Pioneer mobile robot with a Microsoft Kinect sensor for following a pedestrian.     

基于形状上下文和粒子滤波的多目标跟踪

目标跟踪是计算机视觉领域里研究的热点和难点。提出一种基于形状上下文和粒子滤波的多目标跟踪算法,通过在跟踪过程中融入目标检测信息来处理目标进入与离开场景问题和目标重叠与分离问题。首先,采用自适应增强检测算法对视频区域中的目标进行检测;然后,利用形状上下文特征来建立被跟踪目标的外观模型;最后,利用粒子滤波方法进行粒子的选择和目标的跟踪。实验证明,提出的算法能够有效处理目标进入与离开场景的问题和目标重合与分离的问题,在单一背景和复杂背景下都能进行较为准确的跟踪,还能一定程度上处理部分遮挡问题。     

Generating fuzzy rules for target tracking using a steady-stategenetic algorithm

Radar target tracking involves predicting the future trajectory of a target based on its past positions. This problem has been dealt with using trackers developed under various assumptions about statistical models of process and measurement noise and about target dynamics. Due to these assumptions, existing trackers are not very effective when executed in a stressful environment in which a target may maneuver, accelerate, or decelerate and its positions be inaccurately detected or missing completely from successive scans. To deal with target tracking in such an environment, recent efforts have developed fuzzy logic-based trackers. These have been shown to perform better as compared to traditional trackers. Unfortunately, however, their design may not be easier. For these trackers to perform effectively, a set of carefully chosen fuzzy rules are required. These rules are currently obtained from human experts through a time-consuming knowledge acquisition process of iterative interviewing, verifying, validating, and revalidating. To facilitate the knowledge acquisition process and ensure that the best possible set of rules be found, we propose to use an automatic rule generator that was developed based on the use of a genetic algorithm (GA). This genetic algorithm adopts a steady-state reproductive scheme and is referred to as the steady-state genetic algorithm (SSGA) in this paper. To generate fuzzy rules, we encode different rule sets in different chromosomes. Chromosome fitness is then determined according to a fitness function defined in terms of the number of track losses and the prediction accuracy when the set of rules it encodes is tested against training data. The rules encoded in the fittest chromosome at the end of the evolutionary process are taken to be the best possible set of fuzzy rules     

Orientation tracking for outdoor augmented reality registration

Our work stems from a program focused on developing tracking technologies for wide-area augmented realities in unprepared outdoor environments. Other participants in the Defense Advanced Research Projects Agency (Darpa) funded Geospatial Registration of Information for Dismounted Soldiers (Grids) program included University of North Carolina at Chapel Hill and Raytheon. We describe a hybrid orientation tracking system combining inertial sensors and computer vision. We exploit the complementary nature of these two sensing technologies to compensate for their respective weaknesses. Our multiple-sensor fusion is novel in augmented reality tracking systems, and the results demonstrate its utility