搜索资源列表
track.zip
- matlab tracking source code to track a moving object on the scene by using centroid and rectangle method,matlab tracking source code to track a moving object on the scene by using centroid and rectangle method
CKPCA-HOG-SVM
- 为了准确地对监控场景中的运动目标进行语义上的分类，提出了一种基于聚类的核主成分分析梯度方向直方图和二又决策树支持向量机的运动目标分类算法。-In order to accurately monitor the movement of scene targets semantic classification, the clustering based on kernel principal component analysis of gradient direction histograms,
spatial_pyramid_code
- 金字塔匹配算法，包括SIFT特征点的提取，聚类和构造金字塔特征表示，论文参考：Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories matlab代码
stk
- matlab控制利用stk进行实时仿真的连接指令以及一个stk现成的场景仿真-matlab control simulation using real-time connection stk instruction and a ready-made scene simulation stk
Factorization
- Lucas-Kanader-Tomasi Feature Tracker，由运动恢复结构的问题，目的是从一组由摄像机移动获得的图像来恢复一个场景的立体结构。对于这个问题，C.Tomasi和T.Kanade[1]于1992年提出了一种Factorization的方法，可以有效地避免噪声的干扰，同时不会受限于特定的运动模型，例如单纯的平移或是旋转。-Lucas-Kanader-Tomasi Feature Tracker, by the movement to restore the structu
LKTK
- Recovering 3-D structure from motion in noisy 2-D images is a problem addressed by many vision system researchers. By consistently tracking feature points of interest across multiple images using a methodology first described by Lucas-Kanade, a 3-D s
biye
- 基于投票算法的目标跟踪,基于二阶非线性投票的多目标跟踪算法。该算法通过目标匹配得到同一目标在不同帧中的位置，同时利用特征监测来处理目标的遮挡、分裂问题，并实现目标特征的实时更新。在目标匹配过程中，通过对目标前一帧与当前帧的特征相似性进行投票，得到匹配目标。利用视频图像进行实验，结果表明：该方法对噪声、阴影、遮挡、分裂等具有良好的鲁棒性，较好地实现了多目标的跟踪。-The method used object matching to get objects’ position in differe
LaplaceGaussianPyramid
- 运用拉普拉斯高斯金字塔方法进行景象匹配,实验证明该法能满足实时性和准确性.-The use of Gaussian Laplacian pyramid scene matching methods, experimental proof of the Act can satisfy the real-time performance and accuracy.
retmp
- 该法是经过改进的基于象素匹配的方法并且还含有图片,对进行景象匹配的朋友有所帮助-The Act are improved pixel-based matching method and also contains a picture of the scene matching to help a friend
Motion_Detection
- 一个人在视频场景里面走动，可以对其运动轨迹进行捕捉-In the video scene inside of a person walking, you can track its movement to capture
motion
- This project deals with the tracking and following of single object in a sequence of frames and the velocity of the object is determined. Algorithms are developed for improving the image quality, segmentation, feature extraction and for deterring
SIFT-demo
- 不论科研还是应用上都希望可以和人类的视觉一样通过程序自 动找出两幅图像里面相同的景物，并且建立它们之间的对应，前几年才被提出的SIFT（尺度不变特征）算法提供了一种解决方法，通过这个算法可以使得满足一 定条件下两幅图像中相同景物的某些点（后面提到的关键点）可以匹配起来-Both research and application, or want to be like the human visual images by automatically identifying two inside t
matlab
- 单天线联合检测算法的matlab仿真源程序——场景：基站和1用户单天线，TD下行-Single-antenna co-detection algorithm of matlab simulation source code- the scene: the base station and a user single-antenna, TD downlink
scene_text_extraction
- 基于场景的文本定位，使用matlab平台进行图像处理-Scene text localization based on the use of image processing matlab platform
lbp(1)
- 是一种纹理描述算子用于快速提取图像的纹理特征,应用于医学图像检索,场景分类等.-Is a texture descr iption operator for rapid extraction of texture features, used in medical image retrieval, scene classification.
codetsu
- 用来对图像进行分类。Source code for Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework. Computer Vision and Pattern Recognition (CVPR) 2009，Li-Jia Li, Richard Socher and Li Fei-Fei. -Source code for Towards
xx001
- 三维重建技术的研究是计算机视觉学科的一个重要领域，而双目视觉则是三维重建中的一项重要技术，它利用左右摄像机拍摄出的立体图像对，依据其中包含的几何关系将场景的三维信息重构出来。-The 3-D reconstruction technology of computer vision is a significant field of computer vision ,and binocular stereo vision is a very important technique in 3-D
shuangmushijue
- 三维重建技术的研究是计算机视觉学科的一个重要领域，而双目视觉则是三维重建中的一项重要技术，它利用左右摄像机拍摄出的立体图像对，依据其中包含的几何关系将场景的三维信息重构出来。-The 3-D reconstruction technology of computer vision is a significant field of computer vision ,and binocular stereo vision is a very important technique in 3-D
Matlab-Scene-depth-liang
- 计算照相机景深，改变焦距大小，改变光圈大小，可以计算得到的相应景深，包括相关注释-caculate the depth of scene
auditory_scene_classification-master
- 2013 声场景挑战赛 适合作为环境声音分类参考，内含代码。(scene-classification-aasp-2013-master)