Contour level object detection with top-down information

This paper presents a contour level object detection approach. In contrast to conventional bounding box results, we give out the salient closed contour of the object, which provides a possibility of semantic analysis for the object. We get the salient closed contour with Ratio Contour algorithm. The top-down information needed by salient closed contour extraction is based on the well-known Bag-of-Features methodology. Our top-down information based contour extraction and completion is much more efficient and robust than many related approaches lack of the top-down information. We also propose a novel post-processing framework for object detection. With low threshold and a refined binary classifier, we can get stable high performance. We evaluate our approaches on UIUC cars dataset. We show that our approaches apparently improve the performance of object detections under clutter.     

High accurate estimation of relative pose of cooperative space targets based on measurement of monocular vision imaging

Autonomous rendezvous and docking (ARD) plays a very important role in planned space programs, the success of ARD rests with the estimation accuracy and efficiency of relative pose among various spacecraft in rendezvous and docking. In this paper, a high accuracy and efficiency estimation algorithm of relative pose of cooperative space targets is presented based on monocular vision imaging, in which a modified gravity model approach and multiple targets tracking methods are employed to improve the accuracy of feature extraction and enhance the estimation efficiency, meanwhile the Levenberg–Marquardt method (LMM) is used to achieve a well global convergence. Moreover an experimental platform with DSP and FPGA is designed and implemented. The comprehensive experimental results demonstrate its outstanding accuracy and efficiency, the update rate achieves 16 Hz and the estimated error of depth does not exceed 2% with noise influence.     

时变离散切换系统的迭代学习控制

针对一类具有任意切换序列的时变离散切换系统的轨迹跟踪问题,提出了一种离散迭代学习控制算法.该算法在切换序列沿迭代轴不变而只沿时间轴变化的前提下,将整个有限时间区间划分为有限个子区间,并利用λ-范数对各个子区间上的收敛性进行了严格证明,给出了算法收敛的范数形式的充分条件.该方法不仅实现了时变离散切换系统在有限时间内对目标轨迹的完全跟踪,而且结构简单更便于工程实现.仿真结果验证了该方法的有效性.     

概率假设密度滤波的物理空间意义

为了深入理解概率假设密度滤波,本文在Ozgur Erdinc对随机集的物理空间假设的基础上,采用Bayes公式和全概率公式对概率假设密度滤波的迭代过程进行了推导.为有效改善概率假设密度滤波的目标漏检问题提供了理论基础.     

带势估计的概率假设密度滤波的物理空间意义

为了便于人们深入理解带势估计的概率假设密度滤波,本文在Ozgur Erdin对随机集做的物理空间假设的基础上,采用Bayes公式和全概率公式对带势估计的概率假设密度滤波的迭代过程进行了推导.推导过程详细明了,推导结果与文献一致.这为带势估计的概率假设密度滤波在目标跟踪中的应用及性能改进提供了理论基础.     

基于联合仿射不变弧长的目标轮廓起始点配准

提出了一种仿射不变的快速目标轮廓起始点配准算法,为实现快速目标识别开辟了新的思路.该算法利用基于轮廓曲率和轮廓包围面积的两种仿射不变弧长引出特征描述函数,通过其极值点的幅值和相对位置关系引出幅值误差和相对位置误差并结合二者构造出评价函数.通过循环比对和位置临近对应原则找到使评价函数最小的目标轮廓位置点即为配准的起始点.大量实验结果表明该算法具有高起始点配准率、高抗噪能力和低时间复杂度.     

一种鲁棒的目标跟踪方法

针对传统特征光流场跟踪方法中由于误差积累和错误匹配而导致的特征点丢失问题,基于一种新的Harris-SIFT特征点表示方法,提出基于预测帧与关键帧的算法框架,实现了光流场运动估计与局部特征识别相结合的目标跟踪方法.预测帧利用塔式分解和递归算法计算特征点的光流场运动矢量,使用运动矢量直方图获取目标的运动矢量,并剔除误匹配点;当特征点数量小于5个时,关键帧使用Harris-SIFT特征点进行局部特征匹配,利用仿射模型对目标精确定位及姿态修正.实验结果表明,本方法对视频序列中的纹理特征目标跟踪的鲁棒性较好,在背景复杂、目标遮挡或暂时丢失情况下,仍可以继续完成目标的可靠跟踪.     

Trajectory tracking control of variable length pendulum by partial energy shaping

This paper concerns a trajectory tracking control problem for a pendulum with variable length, which is an underactuated mechanical system of two degrees-of-freedom with a single input of adjusting the length of the pendulum. We aim to study whether it is possible to design a time-invariant control law to pump appropriate energy into the variable length pendulum for achieving a desired swing motion (trajectory) with given desired energy and length of the pendulum. First, we show that it is difficult to avoid singular points in the controller designed by using the conventional energy-based control approach in which the total mechanical energy of the pendulum is controlled. Second, we present a tracking controller free of singular points by using only the kinetic energy of rotation and the potential energy of the pendulum and not using the kinetic energy of the motion along the rod. Third, we analyze globally the motion of the pendulum and clarify the stability issue of two closed-loop equilibrium points; and we also provide some conditions on control parameters for achieving the tracking objective. Finally, we show numerical simulation results to validate the presented theoretical results.     

Measuring the kinetic parameters of saltating sand grains using a high-speed digital camera

A high-speed digital camera is used to record the saltation of three sand samples(diameter range:300–500,200–300 and100–125μm).This is followed by an overlapping particle tracking algorithm to reconstruct the saltating trajectory and the differential scheme to abstract the kinetic parameters of saltating grains.The velocity results confirm the propagating feature of saltation in maintaining near-face aeolian sand transport.Moreover,the acceleration of saltating sand grains was obtained directly from the reconstructed trajectory,and the results reveal that the climbing stage of the saltating trajectory represents an critical process of energy transfer while the sand grains travel through air.