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[ActiveX/DCOM/ATLtracking

Description: Below is the combined code in .zip and .tar.gz formats. Please remember all of this a major work in progress and is by no means finished. We should all try to make this site comparable to it s IDL predecessor. We need YOU to write good, well documented code that will make this repository complete. The following is the minimal amount of code needed to filter and locate particles in 2d. The version of track here is fully 3D and the 3D feature and bpass are coming.
Platform: | Size: 18708 | Author: hmk | Hits:

[ActiveX/DCOM/ATLtracking

Description:
Platform: | Size: 18432 | Author: hmk | Hits:

[Othertracing

Description: 航迹划定,加上跟踪,等等哦那功能使的好划定航迹-Track designation, plus tracking, etc. Oh, that' s a good feature to
Platform: | Size: 13312 | Author: chen | Hits:

[Software Engineeringgood-feature-to-track

Description: shi&Tomasi 关于角点检测的经典论文-shi & Tomasi corner detection on the classic paper
Platform: | Size: 803840 | Author: 夏天 | Hits:

[Special Effectsfeature-to-track

Description: 本文研究了用肤色特征跟踪人脸的方法,在最后用matlab仿真实验加以说明本算法的优点-it is a good feature for tracking and show the usefull with matlab
Platform: | Size: 803840 | Author: cathy | Hits:

[ELanguageFreeIMU_Processing_20110724_1448

Description: The main application of FreeIMU is orientation sensing: by reading the data from the various sensors is possible to compute precisely the orientation of FreeIMU in the space. Recent boards also feature an high resolution barometer allowing to precisely track the device altitude. This can be useful in many applications: human-computer interaction device prototyping, flying machines, robots, human movement tracking and everywhere orientation sensing is a key aspect. As FreeIMU breakout the sensors interrupt pins, it s also possible to detect per axis single and double taps, free fall as well as activity or inactivity. This makes FreeIMU a very good choice for Human-Computer devices prototyping. Interrupts pins are also very useful if you are into interrupt based reading of the sensors, useful to develop high frequency interrupt based sensor reading.
Platform: | Size: 76800 | Author: Tran Bao An | Hits:

[Industry researchAccelerometer

Description: The main application of FreeIMU is orientation sensing: by reading the data from the various sensors is possible to compute precisely the orientation of FreeIMU in the space. Recent boards also feature an high resolution barometer allowing to precisely track the device altitude. This can be useful in many applications: human-computer interaction device prototyping, flying machines, robots, human movement tracking and everywhere orientation sensing is a key aspect. As FreeIMU breakout the sensors interrupt pins, it s also possible to detect per axis single and double taps, free fall as well as activity or inactivity. This makes FreeIMU a very good choice for Human-Computer devices prototyping. Interrupts pins are also very useful if you are into interrupt based reading of the sensors, useful to develop high frequency interrupt based sensor reading.
Platform: | Size: 1850368 | Author: Tran Bao An | Hits:

[Special EffectsKTL(1.3.4)

Description: 图像处理中的特征匹配算法,KTL特征跟踪算子的实现。参考论文:Good Features To Track-Image processing feature matching algorithm, KTL feature tracking operator implementations. Reference papers: Good Features To Track
Platform: | Size: 1208320 | Author: 朱继祥 | Hits:

[Audio programB.Lucas

Description: 这是KLT算法论文的高清版。Kanade-Lucas-Tomasi方法,在跟踪方面表现的也不错,尤其在实时计算速度上,用它来得到的,是很多点的轨迹“trajectory”,并且还有一些发生了漂移的点,所以,得到跟踪点之后要进行一些后期的处理,说到Kanade-Lucas-Tomasi方法,首先要追溯到Kanade-Lucas两人在上世纪80年代发表的paper:An Iterative Image Registration Technique with an Application to Stereo Vision,这里讲的是一种图像点定位的方法,即图像的局部匹配,将图像匹配问题,从传统的滑动窗口搜索方法变为一个求解偏移量d的过程,后来Jianbo Shi和Carlo Tomasi两人发表了一篇CVPR(94 )的文章Good Features To Track,这篇文章,主要就是讲,在求解d的过程中,哪些情况下可以保证一定能够得到d的解,这些情况的点有什么特点(后来会发现,很多时候都是寻找的角点)。-KLT is an implementation, in the C programming language, of a feature tracker for the computer vision community. The source code is in the public domain, available for both commercial and non-commerical use. The tracker is based on the early work of Lucas and Kanade [1], was developed fully by Tomasi and Kanade [2], and was explained clearly in the paper by Shi and Tomasi [3]. Later, Tomasi proposed a slight modification which makes the computation symmetric with respect to the two images-- the resulting equation is derived in the unpublished note by myself [4]. Briefly, good features are located by examining the minimum eigenvalue of each 2 by 2 gradient matrix, and features are tracked using a Newton-Raphson method of minimizing the difference between the two windows. Multiresolution tracking allows for relatively large displacements between images. The affine computation that evaluates the consistency of features between non-consecutive frames [3] was implemented by Thorsten T
Platform: | Size: 789504 | Author: 王凯 | Hits:

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