一种基于二分图最优匹配的镜头检索方法

镜头检索是基于内容的视频检索的重要内容.本文首次尝试将二分图的最优匹配用于镜头检索.与现有方法相比,本文提出的方法强调在一一对应的前提下,全面客观地度量两个镜头的相似度.把两个镜头的相似度度量建模为一个带权的二分图:镜头中的每一帧看成二分图的一个结点,两个镜头之间任意帧的相似值作为边的权值.在一一对应的前提下,利用最优匹配的Kuhn-Munkres算法求出该二分图的最大权,以此作为两个镜头的相似度.考虑到检索速度问题,提出了两个改进算法.实验对比结果证实了本文所提方法在镜头检索中的优异表现.     

一种检测足球视频中射门镜头的方法

体育视频中事件的检测是基于内容的体育视频检索的前提.根据足球比赛视频的特点,提出了一种有效的射门镜头检测方法,即利用主颜色区域检测和投影法来检测射门镜头,从而实现了按射门镜头对视频进行检索.最后给出实验结果及分析.     

Robust player detection and tracking in broadcast soccer video based on enhanced particle filter

It is significant to detect and track soccer players in broadcast sports video, which is helpful to analysis player activity and team tactics. However, it is challenging to efficiently detect and track soccer players with shots switched and noise caused by auditorium and billboards. And for multi-player tracking how to treat the increase or decrease of player are also difficult. In this paper, a robust player detection algorithm based on salient region detection and tracking based on enhanced particle filtering are proposed. Salient region detection is used to segment sports fields, and then soccer players are detected by edge detection combined with Otsu algorithm. For soccer players tracking, we use an enhanced particle filter which we improve the algorithm in sample and the likelihood function combing the color feature and edge feature. Experimental results show the proposed algorithm can quickly and accurately detect and track soccer players in broadcast video.     

Study on Optimizing of Ball Passing Strategy and Role Switching Mechanism for Robot Soccer

A new ball passing strategy for robot soccer is proposed in this paper. With introduce of a new algorithm on ball passing, the optimum strategy is confirmed to be more efficient and exact when passing a ball. Questions of role switching in multi-intelligent agent cooperation in robot soccer are described based on Generalized Stochastic Petri-Net （GSPN）. Results of computer simulation have confirmed the feasibility and efficiency of above Petri-net method.     

World modeling on an MSL robotic soccer team

When a team of robots is built with the objective of playing soccer, the coordination and control algorithms must reason, decide and actuate based on the current conditions of the robot and its surroundings. This is where sensor and information fusion techniques appear, providing the means to build an accurate model of the world around the robot, based on its own limited sensor information and the also limited information obtained through communication with the team mates. One of the most important elements of the world model is the robot self-localization, as to be able to decide what to do in an effective way, it must know its position in the field of play. In this paper, the team localization algorithm is presented focusing on the integration of visual and compass information. An important element in a soccer game, perhaps the most important, is the ball. To improve the estimations of the ball position and velocity, two different techniques have been developed. A study of the visual sensor noise is presented and, according to this analysis, the resulting noise variation is used to define the parameters of a Kalman filter for ball position estimation. Moreover, linear regression is used for velocity estimation purposes, both for the ball and the robot. This implementation of linear regression has an adaptive buffer size so that, on hard deviations from the path (detected using the Kalman filter), the regression converges faster. A team cooperation method based on sharing the ball position is presented. Other important data during the soccer game is obstacle data. This is an important challenge for cooperation purposes, allowing the improvement of team strategy with ball covering, dribble corridor estimation, pass lines, among other strategic possibilities. Thus, detecting the obstacles is ceasing to be enough and identifying which obstacles are team mates and opponents is becoming a need. An approach for this identification is presented, considering the visual information, the known characteristics of the team robots and shared localization among team members. The described work was implemented on the CAMBADA team and allowed it to achieve particularly good performances in the last two years, with a 1st and a 3rd place in the world championship RoboCup 2008 and RoboCup 2009 editions, respectively, as well as distinctively achieve 1st place in 2008 and 2009 editions of the Portuguese Robotics Open.     

一种启发式的足球机器人传球路径搜索算法

在机器人足球比赛的动态和不确定环境中,机器人一般选择带球进攻,为了增强比赛的水平和观赏性,可以开发更多的传球策略,这里特别针对前场传切进攻战术,提出了启发式的传球路径搜索算法。该算法考虑了影响传球路线的多方面因素,能在有效时间为持球机器人提供更多的可用传球路线,并生成更好的传球路线。     

一种基于内容表示的图像序列运动分割算法

提出了一种MPEG－4标准所规范的基于内容表示的图像序列运动分割算法。首先进行图像序列二维运动估计并计算位移帧差,然后,将位移帧差作为将运动物体从静止背景中分离出来的标准进行分割;最后对分割结果进行形态滤波。实验结果显示,在物体存在整体运动的情况下,分割结果表现出了很好的准确度,可以成功地提取图像序列中的运动物体。     

基于非线性滤波方法的PIV计算

针对流体运动图像计算(也称为PIV),为了获得可靠的运动矢量场、散度场和旋度场,该文提出了一种基于非线性滤波思想的PIV计算方法。新方法属于变分PIV方法,其在克服传统PIV方法不足的同时避开了经典变分方法中能量范函凸性和可微性的约束,将能量函数的最小化过程转变为非线性滤波过程。该文针对实际粒子图像序列与经典方法进行了实验和比较,结果证明新方法能够在有效抑制噪声的同时可以较好地保持在多流体运动的情况下运动矢量、散度和旋度场的细节信息。     

An efficient omnidirectional vision system for soccer robots: From calibration to object detection

Robotic soccer is nowadays a popular research domain in the area of multi-robot systems. In the context of RoboCup, the Middle Size League is one of the most challenging. This paper presents an efficient omnidirectional vision system for real-time object detection, developed for the robotic soccer team of the University of Aveiro, CAMBADA. The vision system is used to find the ball and white lines, which are used for self-localization, as well as to find the presence of obstacles. Algorithms for detecting these objects and also for calibrating most of the parameters of the vision system are presented in this paper. We also propose an efficient approach for detecting arbitrary FIFA balls, which is an important topic of research in the Middle Size League. The experimental results that we present show the effectiveness of our algorithms, both in terms of accuracy and processing time, as well as the results that the team has been achieving: 1st place in RoboCup 2008, 3rd place in 2009 and 1st place in the mandatory technical challenge in RoboCup 2009, where the robots have to play with an arbitrary standard FIFA ball.     

A robust omnidirectional vision sensor for soccer robots

How to make robot vision work robustly under varying lighting conditions and without the constraint of the current color-coded environment are two of the most challenging issues in the RoboCup community. In this paper, we present a robust omnidirectional vision sensor to deal with these issues for the RoboCup Middle Size League soccer robots, in which two novel algorithms are applied. The first one is a camera parameters auto-adjusting algorithm based on image entropy. The relationship between image entropy and camera parameters is verified by experiments, and camera parameters are optimized by maximizing image entropy to adapt the output of the omnidirectional vision to the varying illumination. The second one is a ball recognition method based on the omnidirectional vision without color classification. The conclusion is derived that the ball on the field can be imaged to be an ellipse approximately in our omnidirectional vision, and the arbitrary FIFA ball can be recognized by detecting the ellipse imaged by the ball. The experimental results show that a robust omnidirectional vision sensor can be realized by using the two algorithms mentioned above.     

Motion artifact cancellation in NIR spectroscopy using Wiener filtering

We present a Wiener filtering based algorithm for the elimination of motion artifacts present in Near Infrared (NIR) spectroscopy measurements. Until now, adaptive filtering was the only technique used in the noise cancellation in NIR studies. The results in this preliminary study revealed that the proposed method gives better estimates than the classical adaptive filtering approach without the need for additional sensor measurements. Moreover, this novel technique has the potential to filter out motion artifacts in functional near infrared (fNIR) signals, too.     

Video scene clustering by graph partitioning

A new video scene clustering method using graph partitioning is proposed. In the method, the shots of a video are grouped into clusters of similar scenes based on shot colour attributes; the number of scene clusters is not required to be known a priori. Experimental results are presented to show the effectiveness of the proposed method.     

Ball localization and tracking in a highly dynamic table soccer environment

This article presents the development of a ball localization and tracking algorithm, that is to be applied in a highly dynamic table soccer environment. The described approach is based on an earlier survey paper on object tracking, where a general selection procedure on object detection and tracking techniques was proposed. Although the survey paper presents a variety of state estimation techniques for tracking, this article describes why these are not well suited for our specific application. For this reason, an IMM estimation technique is adopted that has not been applied in this highly dynamic context before. To evaluate the IMM estimator, it is compared to the well-known and commonly used Kalman filter, that has been optimally tuned for this specific application.     

Analysis and Experimental Verification of a Three-Dimensional Noncontacting Angular Motion Sensor

A three-dimensional noncontacting angular motion sensor, based on magnetometry, has been developed for velocity feedback in the ball wheel mechanism, which serves as the drivetrain for a class of omnidirectional mobile platforms. More generally, this scheme tracks rigid-body rotation about a fixed point with an undefined axis of rotation. The approach involves tracking the time-varying magnetic field of a permanent disc magnet embedded at the center of the sphere. This data is then used to determine the absolute orientation of the magnet axis. Finally, an approach based on the natural invariants of rigid-body motion is used to determine the instantaneous axis of rotation and the angular speed of the sphere about this axis. In this paper, the sensing scheme is formulated, effects of geometric offsets within the tri-axial fluxgate magnetometer are addressed, and results from experimental verification are presented.     

Complexity reduction of digital filters using shift inclusive differential coefficients

We present a graph theoretical methodology that reduces the implementation complexity of the multiplication of a constant vector and a scalar. The complexity of implementation is defined as the required amount of computations like additions. The proposed approach is called minimally redundant parallel (MRP) optimization and is mainly presented in a finite impulse response (FIR) filtering framework to obtain a low-complexity multiplierless implementation. The key idea is to expand the design space using shift inclusive differential coefficients (SIDCs) together with computation reordering using a graph theoretic approach to obtain maximal computation sharing. The problem is formulated using a graph in which vertices and edges represent coefficients and computational cost (number of resources). The multiplierless solution is obtained by solving a set cover problem on the vertices in the graph. A simple polynomial run time algorithm based on a greedy approach is presented. The proposed approach is compared with common-subexpression elimination to show slightly better results and is combined with it for further reduction of complexity. Simulation results show that 50-60% complexity reduction is achieved by only applying the MRP algorithm, and 70% complexity reduction is obtainable by combining it with common-subexpression elimination under a delay constraint of two or three.     

一种新的视频镜头扫换边界检测方法

视频镜头扫换边界是一种常见的镜头边界类型,扫换的特征与大的物体/相机运动相似,比镜头的切变和溶解边界更难检测.本文提出了一种将三维的视频数据转换到二维的时空切片灰度图像,然后利用图像处理算法将扫换边界前后的镜头分割开来.本文提出的方法对大部分扫换类型有效,对扫换镜头边界的长度以及光照的变化不敏感.实验结果表明本文算法能够快速、有效地检测出镜头扫换边界.     

A novel framework for soccer goal detection based on semantic rule

Focusing on the problem of goal event detection in soccer videos, a novel method based on Hidden Markov Model (HMM) and the semantic rule is proposed. Firstly, a HMM for a goal event is constructed. Then a Normalized Semantic Weighted Sum (NSWS) rule is established by defining a new feature of shots, semantic observation weight. The test video is detected based on the HMM and the NSWS rule, respectively. Finally, a fusion scheme based on logic distance is proposed and the detection results of the HMM and the NSWS rule are fused by optimal weights in the decision level, obtaining the final result. Experimental results indicate that the proposed method achieves 96.43% precision and 100% recall, which shows the effectiveness of this letter.     

A New Approach to Motion Pattern Recognition and Its Application to Optical Flow Estimation

In this paper, a new methodology for extracting motion patterns is applied to optical flow estimation in the presence of multiple motions. The proposed approximation deals with the problem in two stages. In the first one, the most important motions are segmented; in the second one, the optical flow is estimated on the basis of the motions detected in the previous stage. To extract relevant motions, a new approach based on a spatio-temporal filtering is presented. The approach groups together parts of a moving object that have been separated into various filter responses because of the object's spatial structure, thereby avoiding the spatial dependency problem associated with a representation based on spatio-temporal filters. The proposed model, therefore, generates one "motion pattern" for each motion detected in the sequence. To obtain an optical flow estimation, which is able to represent multiple velocities, the gradient constraint is applied to the output of each filter so that multiple estimations of the velocity at the same location may be obtained. For each "motion pattern" detected in the previous stage, the velocities at a given point corresponding to the same motion are then combined using a probabilistic approach. In the application to optical flow estimation, the use of "motion patterns" allows multiple velocities to be represented, while the combination of estimations from different filters helps reduce the aperture problem. This technique is illustrated on real and simulated data sets, including sequences with occlusion and transparencies     

A factor graph approach to iterative channel estimation and LDPC decoding over fading channels

This letter provides a comparative study of joint channel estimation and low-density parity-check decoding algorithms for flat Rayleigh fading channels based on the receiver factor graphs. Two approaches for joint channel estimation and decoding are proposed. Intensive simulation studies are carried out to evaluate the receiver sensitivity to the choice of the factor graph. Results show that when channel statistical information is not available at the receiver, a low-pass filtering approach gives a more robust and simpler solution, and it is only 0.5 dB worse than the optimum Wiener filtering. All methods have about 2 dB improvements over the noniterative receivers.