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于 2008-05-05 发布 文件大小:1KB
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说明:  matlab另一中简单些的源码,只给出预测结果,不进行精度分析(Another more simple matlab source code, only the results of prediction are given, not to accuracy analysis)

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    :该文把局部三值模式(Local Ternary Patterns, LTP)纹理特征引入Mean Shift 跟踪算法,提出了基于多 特征的Mean Shift 人脸跟踪算法以解决Mean shift 跟踪算法的鲁棒性问题。通过对LTP 纹理特征的分析、研究, 提出了一个LTP 关键纹理模型,既增强了目标的关键纹理信息,又简化了LTP 纹理模型。在此基础上,提出一 种基于LTP 关键纹理特征和肤色特征的Mean Shift 人脸跟踪算法,有效地解决了Mean Shift 算法的鲁棒性问题。 为进一步提高对快速运动目标的跟踪速度和跟踪性能,该文引入了卡尔曼滤波器对目标进行预测。实验结果表明, 该文的算法在目标定位的准确性和跟踪性能上比Mean Shift 算法均有明显的提高。(: In this paper, the texture characteristics of the local ternary patterns Local Ternary Patterns (LTP) Mean Shift tracking algorithm proposed Mean Shift face tracking algorithm based on multiple features in order to solve the Mean shift tracking algorithm robustness. Texture characteristics of LTP analysis, research, a key LTP texture model, not only enhanced the key goal of texture information, but also simplifies the the LTP texture model. On this basis, based on the LTP key texture features and color characteristics Mean Shift face tracking algorithm, effectively solved the robustness of the Mean Shift algorithm. To further enhance the fast-moving target tracking speed and tracking performance, this paper introduces the Kalman filter to predict the target. The experimental results show that the algorithm of the text in the target positioning accuracy and tracking performance than the Mean Shift algorithm to significantly improve.)
    2012-06-09 09:12:48下载
    积分:1
  • Matlabhanshu
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    曲线拟合和多项式拟合-2,主要用于工程计算,工程优化。(Curve fitting and polynomial fitting, is mainly used for engineering calculations, engineering optimization.)
    2010-06-29 14:06:28下载
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  • junheng
    该程序实现了灰度图像的均衡化处理,是用MATLAB函数直接实现的,较简单(The program achieved the balance of gray image processing is achieved using MATLAB functions direct, simple)
    2010-05-15 08:03:06下载
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    2014-12-04 21:40:36下载
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  • pc_yuan
    线性调频信号(LFM)的脉冲压缩相当于进行匹配滤波,改程序实现该功能。(Chirp signal (LFM) pulse compression is equivalent to the matched filter, change the program to achieve this function)
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