登录
首页 » matlab » image_processing3

image_processing3

于 2021-04-20 发布 文件大小:16996KB
0 251
下载积分: 1 下载次数: 24
我要下载

代码说明：

  图像工程作业3：基于视词袋模型的场景识别 (Scene recognition with bag of words)(Image Engineering Job 3: Scene Recognition Based visual bag of words (Scene recognition with bag of words))

文件列表：

图像工程第三次作业
..................\code
..................\....\build_vocabulary.m,3020,2016-01-21
..................\....\create_results_webpage.m,12308,2016-01-21
..................\....\get_bags_of_sifts.m,3578,2016-01-20
..................\....\get_image_paths.m,1771,2016-01-20
..................\....\get_tiny_images.m,1520,2016-01-21
..................\....\nearest_neighbor_classify.m,2319,2016-01-21
..................\....\proj3.m,8951,2016-01-21
..................\....\svm_classify.m,3185,2016-01-20
..................\....\vlfeat
..................\....\......\.gitattributes,59,2014-09-12
..................\....\......\.gitignore,700,2014-09-12
..................\....\......\apps
..................\....\......\....\phow_caltech101.m,11594,2014-09-12
..................\....\......\....\recognition
..................\....\......\....\...........\encodeImage.m,5278,2014-09-12
..................\....\......\....\...........\experiments.m,6905,2014-09-12
..................\....\......\....\...........\extendDescriptorsWithGeometry.m,822,2014-09-12
..................\....\......\....\...........\getDenseSIFT.m,1679,2014-09-12
..................\....\......\....\...........\readImage.m,919,2014-09-12
..................\....\......\....\...........\setupCaltech256.m,2495,2014-09-12
..................\....\......\....\...........\setupFMD.m,1197,2014-09-12
..................\....\......\....\...........\setupGeneric.m,4024,2014-09-12
..................\....\......\....\...........\setupScene67.m,2368,2014-09-12
..................\....\......\....\...........\setupVoc.m,5189,2014-09-12
..................\....\......\....\...........\trainEncoder.m,6226,2014-09-12
..................\....\......\....\...........\traintest.m,6097,2014-09-12
..................\....\......\....\sift_mosaic.m,4621,2014-09-12
..................\....\......\bin
..................\....\......\...\glnx86
..................\....\......\...\......\aib,8396,2014-09-12
..................\....\......\...\......\libvl.so,293498,2014-09-12
..................\....\......\...\......\mser,21717,2014-09-12
..................\....\......\...\......\sift,26345,2014-09-12
..................\....\......\...\......\test_gauss_elimination,8327,2014-09-12
..................\....\......\...\......\test_getopt_long,8597,2014-09-12
..................\....\......\...\......\test_gmm,13455,2014-09-12
..................\....\......\...\......\test_heap-def,12462,2014-09-12
..................\....\......\...\......\test_host,8345,2014-09-12
..................\....\......\...\......\test_imopv,8611,2014-09-12
..................\....\......\...\......\test_kmeans,8500,2014-09-12
..................\....\......\...\......\test_liop,8389,2014-09-12
..................\....\......\...\......\test_mathop,12490,2014-09-12
..................\....\......\...\......\test_mathop_abs,8450,2014-09-12
..................\....\......\...\......\test_nan,8374,2014-09-12
..................\....\......\...\......\test_qsort-def,12413,2014-09-12
..................\....\......\...\......\test_rand,8386,2014-09-12
..................\....\......\...\......\test_sqrti,8305,2014-09-12
..................\....\......\...\......\test_stringop,12718,2014-09-12
..................\....\......\...\......\test_svd2,8459,2014-09-12
..................\....\......\...\......\test_threads,8669,2014-09-12
..................\....\......\...\......\test_vec_comp,8635,2014-09-12
..................\....\......\...\glnxa64
..................\....\......\...\.......\aib,14080,2014-09-12
..................\....\......\...\.......\libvl.so,370313,2014-09-12
..................\....\......\...\.......\mser,23649,2014-09-12
..................\....\......\...\.......\sift,32519,2014-09-12
..................\....\......\...\.......\test_gauss_elimination,9883,2014-09-12
..................\....\......\...\.......\test_getopt_long,10299,2014-09-12
..................\....\......\...\.......\test_gmm,15335,2014-09-12
..................\....\......\...\.......\test_heap-def,14050,2014-09-12
..................\....\......\...\.......\test_host,9925,2014-09-12
..................\....\......\...\.......\test_imopv,14383,2014-09-12
..................\....\......\...\.......\test_kmeans,10128,2014-09-12
..................\....\......\...\.......\test_liop,9977,2014-09-12
..................\....\......\...\.......\test_mathop,14141,2014-09-12
..................\....\......\...\.......\test_mathop_abs,10078,2014-09-12
..................\....\......\...\.......\test_nan,9962,2014-09-12
..................\....\......\...\.......\test_qsort-def,13977,2014-09-12
..................\....\......\...\.......\test_rand,9966,2014-09-12
..................\....\......\...\.......\test_sqrti,9865,2014-09-12
..................\....\......\...\.......\test_stringop,14376,2014-09-12
..................\....\......\...\.......\test_svd2,14175,2014-09-12
..................\....\......\...\.......\test_threads,14441,2014-09-12
..................\....\......\...\.......\test_vec_comp,14391,2014-09-12
..................\....\......\...\maci
..................\....\......\...\....\aib,9384,2014-09-12
..................\....\......\...\....\libvl.dylib,279560,2014-09-12
..................\....\......\...\....\mser,22636,2014-09-12
..................\....\......\...\....\sift,31248,2014-09-12
..................\....\......\...\....\test_gauss_elimination,9264,2014-09-12
..................\....\......\...\....\test_getopt_long,9388,2014-09-12
..................\....\......\...\....\test_gmm,14416,2014-09-12
..................\....\......\...\....\test_heap-def,21836,2014-09-12
..................\....\......\...\....\test_host,9300,2014-09-12
..................\....\......\...\....\test_imopv,9572,2014-09-12
..................\....\......\...\....\test_kmeans,9452,2014-09-12
..................\....\......\...\....\test_liop,9364,2014-09-12
..................\....\......\...\....\test_mathop,13396,2014-09-12
..................\....\......\...\....\test_mathop_abs,9400,2014-09-12
..................\....\......\...\....\test_nan,9316,2014-09-12
..................\....\......\...\....\test_qsort-def,9276,2014-09-12
..................\....\......\...\....\test_rand,9372,2014-09-12
..................\....\......\...\....\test_sqrti,9232,2014-09-12
..................\....\......\...\....\test_stringop,13612,2014-09-12
..................\....\......\...\....\test_svd2,9416,2014-09-12
..................\....\......\...\....\test_threads,9564,2014-09-12
..................\....\......\...\....\test_vec_comp,9588,2014-09-12
..................\....\......\...\maci64

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • Matching
    数字摄影测量中的最小二乘匹配算法，带示例图像(Feature points matching using LSTM)
    2019-04-22 13:42:21下载
    积分：1
  • dtcwt_toolbox
    经典的双树复小波分解包经典的双树复小波分解包经典的双树复小波分解包(a toolbox of dtcwta toolbox of dtcwta toolbox of dtcwt)
    2021-03-30 20:09:09下载
    积分：1
  • ICM--MRF--matlab
    基于MRF随机场的SAR图像分割 求最优算法ICM matlab语言(Based the MRF with airport SAR image segmentation to seek optimal algorithm ICM matlab language)
    2020-07-01 09:00:02下载
    积分：1
  • src
    说明：  ORB-SLAM 基本延续了 PTAM 的算法框架,但对框架中的大部分组件都做了改进, 归纳起来主要有 4 点: ORB-SLAM 选用了 ORB 特征, 基于 ORB 描述量的特征匹配和重定位, 都比 PTAM 具有更好的视角不变性。此外, 新增三维点的特征匹配效率更高, 因此能更及时地扩展场景。扩展场景及时与否决定了后续帧是否能稳定跟踪。ORBSLAM 加入了循环回路的检测和闭合机制, 以消除误差累积。系统采用与重定位相同的方法来检测回路(匹配回路两侧关键帧上的公共点), 通过方位图 (Pose Graph) 优化来闭合回路。PTAM 需要用户指定 2 帧来初始化系统, 2 帧间既要有足够的公共点, 又要有足够的平移量. 平移运动为这些公共点提供视差 (Parallax) , 只有足够的视差才能三角化出精确的三维位置。ORB-SLAM 通过检测视差来自动选择初始化的 2 帧。PTAM 扩展场景时也要求新加入的关键帧提供足够的视差, 导致场景往往难以扩展. ORB-SLAM 采用一种更鲁棒的关键帧和三维点的选择机制——先用宽松的判断条件尽可能及时地加入新的关键帧和三维点, 以保证后续帧的鲁棒跟踪; 再用严格的判断条件删除冗余的关键帧和不稳定的三维点，以保证 BA 的效率和精度。(Orb-slam basically continues the algorithm framework of PTAM, but most of the components in the framework have been improved, which mainly includes four points:)
    2020-06-11 23:43:54下载
    积分：1
  • zhongxinchafenfa
    详细描述了中心差分法的原理，并举例说明的中心差分法的应用(The principle of the central difference method is described in detail and examples illustrate the application of the central difference method)
    2021-02-21 14:49:42下载
    积分：1
  • inexact_alm_rpca
    RPCA (Robust Principal Component Analysis)是目前用于矩阵填充、图像去噪的最有效的优化方法。目前最有效的算法是ALM（Augmented Lagrange Multiplier）。ALM分为Exact ALM和Inexact ALM。 该代码是Inexact ALM，收敛速度比Exact ALM快！(RPCA (Robust Principal Component Analysis) is used for matrix filling, image denoising. It is currently the most effective optimization method. Currently the most effective method is ALM (Augmented Lagrange Multiplier). There re 2 kinds of ALM: Exact ALM and Inexact ALM. The code is Inexact ALM, faster convergence speed than the Exact ALM!)
    2010-11-02 14:07:29下载
    积分：1
  • FisheyeImCorr
    图片鱼眼畸变校正程序。用于处理图片桶形失真枕形失真。(Picture fisheye distortion correction program. Used for processing images barrel distortion pincushion distortion.)
    2012-10-12 14:38:29下载
    积分：1
  • Neural-Network-pattern-recognition
    说明：  bp人工神经网络模式识别教程示例，研究人脸识别 手势识别有帮助(bp nervel network trainning and recognition ,e.g:face & dynamic hand gesture detection and face recognition .I hope it would be very useful for researcher !)
    2009-08-02 10:51:30下载
    积分：1
  • Nonlocal-Image-Restoration-
    利用非局部特性并结合低秩解法的图像降噪算法，速度很快(Nonlocal properties combined with low rank Solution image noise reduction algorithm, fast)
    2021-04-25 11:48:46下载
    积分：1
  • PowerMaxImageFusion
    说明：  图像融合是图像处理的一个研究热点，这里提供一种方法即局部能量最大选取规则图像融合法(Image fusion is image processing of a research hot spot that is here to provide a way to select the rules of the local energy of the largest image fusion method)
    2008-11-08 19:11:16下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！