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Some code for tracking color object base on opencv library
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Work in progress implementation of multiple object recognition using color, location, edge and texton-layout filters. Uses OpenCV 2.0
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Uses blender to generate a scene with reference objects. Takes input images and uses opencv methods to estimate the object translation and rotation from the camera. Reads the object 3D coordinates from a file and uses color to detect the objects in t
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基于OPENCV的鼠标模拟控制程序。根据目标物体的颜色执行对应的鼠标动作。红色控制鼠标移动，绿色和蓝色对应左右键。-Based on the OPENCV mouse analog control program. Performed according to the color of the target object corresponding to the mouse action. Red control mouse movement, green and blue correspond
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是opencv的c++常用的所有的程序，包括人脸识别，运动物体跟踪，颜色识别，图形图像设计，摄像头定标等。-Is opencv c++ commonly used all programs, including face recognition, moving object tracking, color recognition, image design, camera calibration, etc.
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如果要跟踪的物体颜色和背景色有较大区别，可用基于颜色的跟踪 如CAMSHIFT 鲁棒性都是较好的。 此源码是一个opencv自带的CamShift算法使用工程实例（有非常详细的注释）。该实例的作用是跟踪摄像头中目标物体，目标物体初始位置用鼠标指出，其跟踪窗口大小和方向随着目标物体的变化而变化。-If you want to track the object color and background color is quite different, color-based tracking is
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Retinex理论的基础理论是物体的颜色是由物体对长波（红色）、中波（绿色）、短波（蓝色）光线的反射能力来决定的，而不是由反射光强度的绝对值来决定的，物体的色彩不受光照非均匀性的影响，具有一致性，即retinex是以色感一致性（颜色恒常性）为基础的。不同于传统的线性、非线性的只能增强图像某一类特征的方法，Retinex可以在动态范围压缩、边缘增强和颜色恒常三个方面打到平衡，因此可以对各种不同类型的图像进行自适应的增强。-The basic theory of Retinex theory is
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通过opencv实现彩色目标追踪，实现物体图像识别-Opencv track to achieve goals through color, to achieve the object image recognition
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opencv下实现基于均值漂移的追踪技术，运行程序是，用鼠标框选择一个有颜色的物体，可以对它进行追踪操作-Opencv under the mean shift based tracking technology, running the program is to use the mouse to a color object, you can track the operation
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测试特定颜色的物体 ，通过 hsv转rgb，然后选取红色(Test a specific color object, pass HSV to RGB, and then select red)
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Hand Detection Using Color Recognition Object Tracking and Gesture Recognition
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