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Detecting, identifying, and recognizing salient regions or feature points
in images is a very important and fundamental problem to the computer vision
and robotics community. Tasks like landmark detection and visual odometry,
but also object re
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用CRF实现的名称物体识别的程序，对于初学模式识别的人很好-With CRF to achieve the name of the object recognition procedure were very good for the beginner pattern recognition
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本文提出了一种新的方法探讨其在镜面物体识别的作用，使用照明代表的球形谐波。 -In this paper, we propose a new method to enforce this constraint and explore its usefulness in specular object recognition, using the spherical harmonic representation of lighting.
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基于NewMikolajczykDetector产生的.sift文件的特征点匹配！-Image matching and object recognition Based on .sift file generated by NewMikolajczykDetector
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运用Opencv视频图像处理库编写的离线签名识别，首先选取16个签名做训练样本，再对剩下的样本进行测试-The use of video image processing library Opencv prepared off-line signature recognition, first select the 16 signatures to do the training samples, and then the remaining samples for testing
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VC 2005 人脸识别源代码， 用于图像分割和目标识别， 这是书上的例程-VC 2005 face recognition source code, for image segmentation and object recognition, which is routine in a book
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图像分类软件，用MATLAB语言编写，可实现对象的分类和匹配识别-Image classification software used MATLAB language, enabling the object classification and matching recognition
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国外的一个进行图像图形直线化的代码，能够对人脸和汽车图片进行直线化处理。-Many recognition algorithms depend on careful positioning of an object into a canonical pose, so the position of features relative to a fixed coordinate system can be examined. Generally, this positioning is done
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OpenCV 人脸识别示例，请将源码拷贝至E盘（具体路径，参见编译后提示）
请使用Debug模式编译-OpenCV Face Recognition sample, please copy the source code to the E site (the specific path, see the compiled tips), please use the Debug mode compilation
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Semi-Local Affine Parts for Object Recognition
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Object recognition from local scale-invariant features
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去的十年，通过实验手段，已积累灵长类视觉皮层的大量实验数据．许多研究者根据这些实验数据提
出动物视觉系统的模型，并将它们用于计算机目标识别．文中首先总结动物视觉系统的主要实验结论，然后评述基
于灵长类视觉系统工作机制的常用模型，重点讨论MIT的皮层等级模型．-Object Recognition Models Based on Primate Visual Cortices
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1. 实验目的
⑴掌握有自平衡能力的热工对象的几种辨识方法
⑵掌握掌握数值积分法在有自平衡能力的对象的辨识中的应用，加深对系统辨识的理解和应用。
2. 实验内容
用数值积分法辨识系统参数，结果表示形式为Ф（s）= ，即根据未知系统的输入输出数据求取n,k,T0。输入数据格式为二进制文件，输出为n,k,To具体数值及系统响应曲线。程序运行时画出未知系统的输入输出曲线与辨识得到的参数生成的输入输出曲线对比，就可以得到此种辨识方法的准确度。
-1. ⑴ grasp the pur
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给予捆绑物体的识别！ 给予捆绑物体的识别！ -Object recognition for bundling! Object recognition for bundling! Object recognition for bundling! Object recognition for bundling!
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形状特征是武器装备目标识别的关键因素。针对归一化后轴夹角的特点和小波描述子多尺度描述轮廓曲
线的特性，提出一种R树索引的分层检索技术模型，在模型库空间逐级过滤出与目标相似的模板，以保证检索的效
率和准确性，并通过对军用车辆的检索实验验证了模型的有效性。-The shape features of military weapons＆equipment are the most important key factors of image
object recognition．Aimin
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我收集的基于Haar的对象识别的一些中文论文，结合起来看可以方便理解-I collect Haar-based object recognition in a number of Chinese papers, combined, can easily understand
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Scale Invariant Feature Transform (SIFT) has shown to be very powerful for general object detection/recognition. And recently, it has been applied in face recognition. This is the matlab code.
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facilitate the user s task. One such approach is the
object-related image retrieval. In the context of face
images, it is of interest to retrieve images based on
people s names and facial expressions. However, when
images of the database a
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自适应逆控制技术Simulink程序。可用于全频段振动隔离。需要离线对象辨识。可运行-Adaptive Inverse Control Technology Simulink program. Vibration isolation for the whole band. Require off-line object recognition. Can run
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1 绪论
2 数字图像基础
3 空间域图像增强
4 频率域图像增强
5 图像复原
6 彩色图像处理
7 小波变换和多分辨率处理
8 图像压缩
9 形态学图像处理
10 图像分割
11 表示与描述
12 对象识别-1 Introduction 3 2 digital image based on spatial frequency domain image enhancement image enhancement 4 5 6 Color image p
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