Fast simulation of the forward tracking detector of HPLUS

The necessity of installing a forward tracking detector stack is discussed for the Hadron Physics LanzhoU Spectrometer(HPLUS). A local tracker is developed to solve the multi-track finding problem. The track candidates are searched iteratively via Hough Transform. The fake tracks are removed by a least square fitting process. With this tracker we have studied the feasibility of pp -> pp + phi(-> K+K-), a typical physical channel proposed on HPLUS. The single track momentum resolution due to the uncertainty of the positioning in FTD is 1.3%. The multiple scattering effect contributes about 20% to the momentum resolution in the FTD coverage. The width and the signal-to-background ratio of the reconstructed phi are 1.51 MeV and 4.36, respectively, taking into account the direct Kaon channel pp -> pp + K+K- as background. The geometry coverage of FTD for phi events is about 85.4%. Based on the current fast simulation and estimation, the geometrical configuration of FTD meets the physical requirement of HPLUS under the current luminosity and multiplicity conditions. The tracker is applicable in the full simulation coming next and is extendable to other tracking component of HPLUS.

基于直方图插值的均值移动小尺寸目标跟踪算法

小尺寸目标跟踪是视觉跟踪中的难题。该文首先指出了均值移动小尺寸目标跟踪算法中的两个主要问题:算法跟踪中断和丢失跟踪目标。然后,论文给出了相应的解决方法。对传统Parzen窗密度估计法加以改进,并用于对候选目标区域的直方图进行插值处理,较好地解决了算法跟踪中断问题。论文采用Kullback-Leibler距离作为目标模型和候选目标之间的新型相似性度量函数,并推导了其相应的权值和新位置计算公式,提高了算法的跟踪精度。多段视频序列的跟踪实验表明,该文提出的算法可以有效地跟踪小尺寸目标,能够成功跟踪只有6×12个像素的小目标,跟踪精度也有一定提高。

Non-goal scene analysis for soccer video

The broadcast soccer video is usually recorded by one main camera, which is constantly gazing somewhere of playfield where a highlight event is happening. So the camera parameters and their variety have close relationship with semantic information of soccer video, and much interest has been caught in camera calibration for soccer video. The previous calibration methods either deal with goal scene, or have strict calibration conditions and high complexity. So, it does not properly handle the non-goal scene such as midfield or center-forward scene. In this paper, based on a new soccer field model, a field symbol extraction algorithm is proposed to extract the calibration information. Then a two-stage calibration approach is developed which can calibrate camera not only for goal scene but also for non-goal scene. The preliminary experimental results demonstrate its robustness and accuracy. (c) 2010 Elsevier B.V. All rights reserved.

Incremental pairwise discriminant analysis based visual tracking

The distinguishment between the object appearance and the background is the useful cues available for visual tracking in which the discriminant analysis is widely applied However due to the diversity of the background observation there are not adequate negative samples from the background which usually lead the discriminant method to tracking failure Thus a natural solution is to construct an object-background pair constrained by the spatial structure which could not only reduce the neg-sample number but also make full use of the background information surrounding the object However this Idea is threatened by the variant of both the object appearance and the spatial-constrained background observation especially when the background shifts as the moving of the object Thus an Incremental pairwise discriminant subspace is constructed in this paper to delineate the variant of the distinguishment In order to maintain the correct the ability of correctly describing the subspace we enforce two novel constraints for the optimal adaptation (1) pairwise data discriminant constraint and (2) subspace smoothness The experimental results demonstrate that the proposed approach can alleviate adaptation drift and achieve better visual tracking results for a large variety of nonstationary scenes (C) 2010 Elsevier B V All rights reserved

A Video Quality Assessment Metric Based on Human Visual System

It is important for practical application to design an effective and efficient metric for video quality. The most reliable way is by subjective evaluation. Thus, to design an objective metric by simulating human visual system (HVS) is quite reasonable and available. In this paper, the video quality assessment metric based on visual perception is proposed. Three-dimensional wavelet is utilized to decompose video and then extract features to mimic the multichannel structure of HVS. Spatio-temporal contrast sensitivity function (S-T CSF) is employed to weight coefficient obtained by three-dimensional wavelet to simulate nonlinearity feature of the human eyes. Perceptual threshold is exploited to obtain visual sensitive coefficients after S-T CSF filtered. Visual sensitive coefficients are normalized representation and then visual sensitive errors are calculated between reference and distorted video. Finally, temporal perceptual mechanism is applied to count values of video quality for reducing computational cost. Experimental results prove the proposed method outperforms the most existing methods and is comparable to LHS and PVQM.

Biologically Inspired Features for Scene Classification in Video Surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.

双模式相关技术研究与实现

文中研究的相关跟踪技术主要应用于飞航导弹的末制导。现阶段，激光制导技术、GPS制导技术、合成孔径雷达（SAR）制导技术在我国的实际应用还不成熟，传统的电视、红外制导技术仍然具有很强的生命力，因而，基于可见光的视频相关跟踪技术具有重要的研究价值。本文主要论述的两种相关算法是：多灰度点相关（MPC）、区域模板相关（RTC）。其中多点相关（MPC）算法的跟踪灵敏度高，定位精度好，硬件实现比较方便，实时性能好；区域模板相关算法（RTC），在图像的匹配过程中，不仅考虑了目标区域的灰度特征，而且兼顾了区域里多灰度层次的位置特征、面积特征，算法具有很好的鲁棒性。文中深入研究了两种相关跟踪算法，并针对它们在实际应用中的不足，提出了有效的改善措施。最后，本文对两种相关跟踪算法进行了初步融合，一是：通过粗匹配、精匹配过程来选取目标跟踪点；二是：提出了一种度量模板更新的能量准则函数。大量的仿真实验结果表明：改进后的两种相关跟踪技术可以较好地完成一些复杂背景下的目标跟踪任务，两种算法的有效结合又进一步提高了目标跟踪的稳定性能和可靠性能。本文研究的一些相关跟踪技术已经运用到实际工程项目中。

基于主动视觉和超声的机器人目标跟踪系统

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。

交通监控系统中运动目标分类和跟踪研究

文章讲述了交通监控系统中应用视频图像流来跟踪运动目标并对目标进行分类的具体过程和原则.基于目标检测提出了双差分的目标检测算法,目标分类应用到了连续时间限制和最大可能性估计的原则,目标跟踪则结合检测到的运动目标图像和当前模板进行相关匹配.实验结果表明,该过程能够很好地探测和分类目标,去除背景信息的干扰,并能够在运动目标部分被遮挡、外观改变和运动停止等情况下连续地跟踪目标.