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Description: 提出一种人体运动跟踪算法,从无关节标记的单目视频中获取人体运动1 利用一个带外观模板的人体关节
模型,通过学习得到的运动模型及基于外观模型的相似性计算,巧妙地利用粒子滤波的概率密度传播策略鲁棒地跟
踪普通单目视频中的人体运动1 当出现跟踪丢失时,能在后续序列中自动恢复正确跟踪,且能较好地处理遮挡和自
遮挡问题1 实验表明,该算法鲁棒性好,跟踪结果令人满意- In this paper , a novel approach is proposed for t racking markerless human motion in monocular
videos to capture the articulate motion data1 With an articulated human model const ructed , the new ap2
proach uses the probability density propagation of the particle filters through the learnt motion model and
likelihood computing with the appearance models to t rack the human motion1 The method is capable of auto2
matically recovering f rom t racking failures1 It can also process the occlusion and auto2occlusion problem cor2
rectly1 Experimental result s f rom real monocular videos show that the new approach is robust and the t rack2
ing result s are satisfactory1
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Size: 355328 |
Author: 丁行 |
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Description: 无标识物的增强现实，实时跟踪，具有一定的鲁棒性-This paper addresses the problem of markerless real-
time augmented reality (AR). Many different types of sen-
sors have been used to achieve this including : GPS, gy-
roscopes, cameras, hybrid vision, accelerometers and many
more which have been summarized in [1, 2].
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Size: 804864 |
Author: pgt |
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Description: Markerless AR Demo Program-It was created by others.
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Size: 1463296 |
Author: treven jack |
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Description: HandyAR 这是一篇SigGRAPH的论文。全名为《Handy AR：Markerless Inspection of Augmented Reality Objects Using Fingertip Tracking》-HandyAR This is a SigGRAPH papers. Full name is " Handy AR: Markerless Inspection of Augmented Reality Objects Using Fingertip Tracking"
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Size: 2977792 |
Author: 艳艳 |
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Description: 无标跟踪的库和实现。输出在Debug目录下。需要配置opencv和glew的库。-implementation of markerless tracking. Output in the Debug directory. Need to configure opencv and glew library.
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Size: 36628480 |
Author: 王琢 |
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Description: 手指识别判定 源代码和论文 这个是基于Opencv
详细算法流程，请看论文说明
-Handy AR: Markerless Inspection of Augmented Reality Objects
Using Fingertip Tracking
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Size: 5806080 |
Author: sjc |
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Description: Markerless AR using OpenCV
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Size: 5775360 |
Author: Nick |
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Description: 無標記擴增實境實驗平台建置與追蹤技術驗證所使用的開發環境建立，也就是ARStudio環境的建立
-Markerless Augmented Reality Platform Design and Verification of Tracking Technologies.
ARStudio environment document.
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Size: 1420288 |
Author: 鍾德煥 |
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Description: 目前擴增實境技術相關應用大部分以使用標記為主，但各式應用需求與日俱增，無標記(markerless)擴增實境技術使用上更具彈性，不必受限於標記的使用，因此應用層面更廣。視覺追蹤技術是擴增實境系統重要底層核心技術之一，但使用視覺追蹤技術在實際應用上易受到追蹤物件本身及外觀變化之影響，因此本文提出適用於無標記擴增實境應用之物件追蹤方法，能有效追蹤各式真實物件。首先框選設定追蹤物件；接著擷取物件特徵值，藉由特徵值比對以持續追蹤物件，並利用金字塔L-K光流法以縮短比對運算時間；最後經由2D-3D座標轉換，將3D虛擬物件疊加至真實場景。經由實驗證明本文所提之方法能有效追蹤各式真實物件，並能適用於無標記擴增實境相關應用。-Augmented Reality technology currently most relevant applications to use mark-based, but the increasing demand for all kinds of applications, without marking (markerless) amplification technology more flexible use of reality, not necessarily limited to the use of tags, therefore the application level broader. Visual tracking technology is one of the important augmented reality system underlying core technology, but the use of visual tracking technology in practical applications susceptible to track changes and appearance of the object itself, and therefore in this paper applies to Amplification unmarked objects of reality application tracing method can effectively track all kinds of real objects. First, set the track object marquee then retrieve objects eigenvalues by eigenvalue than to keep track of objects, and uses of the pyramid LK optical flow method to shorten the computation time than on and finally converted via 2D-3D coordinates of the 3D virtual object superimposed to the r
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Size: 644096 |
Author: 鍾德煥 |
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Description: 平面场景的无标记跟踪。这是一篇pdf格式的会议文章-Markerless Tracking using Planar Structures in the Scene
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Size: 2869248 |
Author: 周璐 |
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Description: Zhang et al. - 2015 - A markerless human-manipulators interface using multi-sensors
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Size: 311296 |
Author: Anna |
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