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[Documents] Pedestrian Detection and Tracking for Counting Applications DL : 0: This paper describes a vision based pedestrian detection and tracking system which is able to count people in very crowded situations like escalator entrances in underground stations. The proposed system uses motion to compute regions of interest and prediction of movements, extracts shape information from the video frames to detect individuals, and applies texture features to recognize people. A search strategy creates trajectories and new pedestrian hypotheses and then filters and combines those into accurate counting events. We show that counting accuracies up to 98 % can be achieved.
Date : 2010-12-15 Size : 2.02mb User : harleych
[Documents] TRACKING IN STREAMED VIDEO BY UPDATING GLOBALLY OPTIMAL MATCHINGS DL : 0: Matching methods such as the Hungarian algorithm have recently made an appearance as an alternative to classical tracking algorithms in computer vision, since they are able to nd the set of tracks that optimizes well-dened criteria over a given video sequence. How- ever, despite being globally optimal, they carry a cost: since they require complete knowledge of the sequence, such methods can- not work with continuous video streams, a crucial requirement of realistic video surveillance applications. We were able to use the recently proposed Dynamic Hungarian Algorithm in an innovative way, adapting it to the well-known sliding window methodology. The algorithm is able to run in real-time, while retaining its opti- mality. We tested our implementation on several datasets, tracking humans and vehicles, and obtained reliable results using the same set of parameters on all sequences.
Date : 2011-05-19 Size : 339.78kb User : kongsuhongbaby@126.com
[Documents] object_tracking_lecture DL : 0: 这是目标跟踪系列讲座的一部分，大家共同学习吧-This is the tracking part of a series of lectures, we learn together it
Date : 2026-01-02 Size : 1.87mb User : guanchun
[Documents] ASPeCT DL : 0: 本源代码给出了伽利略卫星导航系统的码跟踪算法-source code is the Galileo satellite navigation system code tracking algorithm
Date : 2026-01-02 Size : 1kb User : sun
[Documents] KernelTracking DL : 0: 详细的介绍了一种经典的跟踪算法，并给出了其他的跟踪算法-detailed account of a classical tracking algorithm, and gives the other tracking algorithm
Date : 2026-01-02 Size : 2.66mb User : 李治国
[Documents] PFe DL : 0: PARTICLE FILTER ON THE TARGET TRACKING .
Date : 2026-01-02 Size : 42kb User : haiser
[Documents] BeyondtheKalmanFilterParticlefilterfortrackingappl DL : 0: 优于Kalman滤波的粒子滤波在目标跟踪中的应用，幻灯片-Kalman filtering is superior to the particle filter in the target tracking application, slide
Date : 2026-01-02 Size : 421kb User : zhao xiaowei
[Documents] jianceyugenzongjishu DL : 0: 基于视频的车辆检测与跟踪技术综述 ^_^-Video-based vehicle detection and tracking technology ^ _ ^
Date : 2026-01-02 Size : 384kb User : 空空空
[Documents] MPPT DL : 0: 开发太阳能发电,最重要的是MPPT,即最大功率点跟踪和并网逆变技术,此英文资料分折独到-The development of solar power generation, the most important thing is MPPT, or maximum power point tracking and grid inverter technology, this data analysis unique in English
Date : 2026-01-02 Size : 154kb User : 人民币
[Documents] VisualTrackingBasedOnObjectAppearanceModeling DL : 0: Visual Tracking Based On Object Appearance Modeling，中国科学院自动化实验室关于基于目标表观建模的视频跟踪-Visual Tracking Based On Object Appearance Modeling, Automation, Chinese Academy of Sciences Laboratory of the apparent object-based modeling on video tracking
Date : 2026-01-02 Size : 1.11mb User : bupt
[Documents] gjlzlv DL : 0: 基于改进粒子滤波的多目标跟踪算法研究，基于改进粒子滤波的多目标跟踪算法研究。-Based on improved particle filter for multi-target tracking algorithm, based on improved particle filter for multi-target tracking algorithm.
Date : 2026-01-02 Size : 1.81mb User : ajie
[Documents] MultitargetTrackinginClutter DL : 0: 本文是多目标跟踪研究的前沿进展，对从事雷达数据处理及信息融合的人具有很好的参考价值，切勿用作商业目的！-This article is a multi-target tracking progress in the forefront of research, engaged in radar data processing and information fusion have a very good reference value, not used for commercial purposes!
Date : 2026-01-02 Size : 807kb User : 侯永华
[Documents] FaceDetectionandHeadTrackinginVideo DL : 0: 清华大学学位论文；将树状多视角人脸检测器引入粒子滤波器的概率跟踪框架，提出了一种融合了检测信息的跟踪方法；对粒子滤波器的基本算法作扩展，提出了一种融合不同状态量的多个观测模型的方法-Degree Thesis, Tsinghua University the tree multiview face detection probability of the introduction of particle filter tracking framework, a combination of detection methods of tracking information of the basic particle filter algorithm, for the extension, a fusion different states than the volume of observation model
Date : 2026-01-02 Size : 1.4mb User : 田卉
[Documents] OnTrackingofMovingObjects DL : 0: 学位论文；运动物体跟踪方法主要包括卡尔曼滤波，Mean-shift，Camshifi算法，粒子滤波器，Snake模型等；应用卡尔曼滤波方法设计了一套煤矿矿工出入自动监测系统；提出了一种新的基于高斯混合模型的颜色特征提取方法，该方法克服了现有的Camshift算法Continuousl y Adaptive eanshift中跟踪目标特征提取精确度低和计算复杂度高的缺陷-Dissertation moving object tracking methods include Kalman filtering, Mean-shift, Camshifi algorithm, particle filter, Snake model the application of Kalman filtering method designed a coal miners out of automatic monitoring system a new Gaussian mixture model based on the color feature extraction method to overcome the existing Camshift algorithm Continuousl y Adaptive eanshift track target feature extraction accuracy and low computational complexity and high defects
Date : 2026-01-02 Size : 1.28mb User : 田卉
[Documents] ResearchOnKeyTechnologiesOfRobustFaceTrackingSyste DL : 0: 鲁棒人脸跟踪系统学位论文；提出了一种两阶段的光照均衡的方法来消除单幅图像中的各种阴影包括模糊阴影，投射阴影等根据快速的Adaboost 训练框架，本文提出了一个实时的鲁棒人脸检测算法提出了一种基于在线实值boosting 的方法来处理人脸在跟踪过程中发生的外貌变化；实现了一个基于以上模块的完全自动化的人脸跟踪器-Robust Face Tracking System dissertation proposes a two-stage light-balanced approach to the elimination of single image in a variety of shadow including fuzzy shadow, projected shadow, etc. Under the fast-track the Adaboost training framework, this paper presents a real-time Robust Face Detection Algorithm Based on boosting online real ways to deal with people face in tracking occurred during the appearance of change the realization of a module based on the above fully automated face tracker
Date : 2026-01-02 Size : 1.09mb User : 田卉
[Documents] BasedOnMeanShiftAndParticleFilterObjectTracking.ra DL : 0: 基于Mean Shift算法和Particle Filter算法的目标跟踪学位论文：讨论了MeanS hift算法(均值偏移)和粒子滤波算法(Particle Filter)，分析了两种算法的特点；，分析了用运动目标检测提取目标运动特征的技术，通过增加对目标特征描述信息，提高跟踪健壮性，并在以颜色直方图描述颜色特征的基础上，融合了目标的运动特征，设计了一种基于运动特征和颜色特征多特征融合的粒子滤波跟踪方法；用二阶直方图描述颜色特征，设计了均值偏移和粒子滤波相结合的目标跟踪技术-Based on Mean Shift Algorithm and Particle Filter algorithm for target tracking dissertation: The MeanS hift algorithm (average deviation) and particle filter (Particle Filter), an analysis of the characteristics of two algorithms analyzed by extracting the target moving target detection Movement characteristics of technology, by increasing the characterization of target information to enhance the tracking robustness, and to describe the color characteristics of color histogram, based on the integration of the target movement characteristics, designed a campaign based on the characteristics and color characteristics of multi-feature integration of particle filter tracking method with second-order description of the color histogram features, designed to offset the mean particle filter and a combination of target tracking technology
Date : 2026-01-02 Size : 2.03mb User : 田卉
[Documents] feature_based_eye_tracking DL : 0: feature based eye tracking docs
Date : 2026-01-02 Size : 602kb User : mircea
[Documents] real_time_3dobject_tracking DL : 0: The paper describes a new robust real time algorithm for 3D object tracking in a video sequences.
Date : 2026-01-02 Size : 672kb User : roboter
[Documents] tracking DL : 0: This paper proposes a new method of extracting and tracking a nonrigid object moving while allowing camera movement. For object extraction we first detect an object using watershed segmentation technique and then extract its contour points by approximating the boundary using the idea of feature point weighting. For object tracking we take the contour to estimate its motion in the next frame by the maximum likelihood method. The position of the object is estimated using a probabilistic Hausdorff measurement while the shape variation is modelled using a modified active contour model. The proposed method is highly tolerant to occlusion. Because the tracking result is stable unless an object is fully occluded during tracking, the proposed method can be applied to various applications.
Date : 2026-01-02 Size : 2.06mb User : sacoura31
[Documents] ContourTracking(2) DL : 0: Contour Tracking paper
Date : 2026-01-02 Size : 494kb User : jack

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