Search - The C Programming Language

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[Audio program] c-music DL : 0: 关于c语言的音乐编程，编制曲目为“枉凝眉”基于基本平台，可再其基础上编制其它音乐-on c language music programming, the preparation of the program of "Lament" on the basic platform, can be further developed on the basis of its other music
Date : 2008-10-13 Size : 1.42kb User : 一杯沧海
[Audio program] c-music DL : 0: 关于c语言的音乐编程，编制曲目为“枉凝眉”基于基本平台，可再其基础上编制其它音乐-on c language music programming, the preparation of the program of "Lament" on the basic platform, can be further developed on the basis of its other music
Date : 2025-12-19 Size : 1kb User : 一杯沧海
[Audio program] sound-echo DL : 0: 根据回声音效的声学原理，使用c语言进行编程，实现回声音效。适合数字信号处理方向的爱好者学习使用。-According to the acoustic echo sound principles, using the c language programming, echo sound. Direction for digital signal processing enthusiasts learn to use.
Date : 2025-12-19 Size : 2kb User : robin
[Audio program] sound-reverb DL : 0: 根据混响音效的声学原理，使用c语言编程实现了混响音效。适合数字信号处理方向的爱好者学习使用。-According to the acoustic reverberation sound principles, using the c language programming to realize the reverb sound. Direction for digital signal processing enthusiasts learn to use.
Date : 2025-12-19 Size : 3kb User : robin
[Audio program] B.Lucas DL : 1: 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which makes the computation symmetric with respect to the two images-- the resulting equation is derived in the unpublished note by myself [4].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
Date : 2025-12-19 Size : 771kb User : 王凯