文件名称:scene_labeling_cvpr2012_v1
- 所属分类:
- 图形图像处理(光照,映射..)
- 资源属性:
- [Matlab] [源码]
- 上传时间:
- 2016-05-05
- 文件大小:
- 27.04mb
- 下载次数:
- 0次
- 提 供 者:
- 李**
- 相关连接:
- 无
- 下载说明:
- 别用迅雷下载,失败请重下,重下不扣分!
介绍说明--下载内容均来自于网络,请自行研究使用
基于场景的超像素图像分割,可以实现快速分割,基于深度信息和颜色信息的检测-Based on ultra-pixel image to divide the scene, you can achieve rapid segmentation, detection based on the depth information and the color information
(系统自动生成,下载前可以参看下载内容)
下载文件列表
scene_labeling_cvpr2012
.......................\nyu_depth
.......................\.........\DATASET.txt
.......................\.........\data_split
.......................\.........\..........\train_10.txt
.......................\.........\..........\train_02.txt
.......................\.........\..........\test_07.txt
.......................\.........\..........\test_08.txt
.......................\.........\..........\train_09.txt
.......................\.........\..........\test_02.txt
.......................\.........\..........\test_05.txt
.......................\.........\..........\all.txt
.......................\.........\..........\test_09.txt
.......................\.........\..........\test_06.txt
.......................\.........\..........\train_04.txt
.......................\.........\..........\train_07.txt
.......................\.........\..........\train_08.txt
.......................\.........\..........\test_01.txt
.......................\.........\..........\test_10.txt
.......................\.........\..........\train_01.txt
.......................\.........\..........\train_03.txt
.......................\.........\..........\train_06.txt
.......................\.........\..........\train_05.txt
.......................\.........\..........\test_03.txt
.......................\.........\..........\test_04.txt
.......................\.........\nyu_data_depths_raw_mask250.mat
.......................\.........\convert_dataset.m
.......................\code
.......................\....\compute_mapping_segmentation.m
.......................\....\compute_features_baseseg_stanford.m
.......................\....\pcnormal.m
.......................\....\get_segment_label.m
.......................\....\compute_features_baseseg_nyu_depth.m
.......................\....\collect_superpixel_features_stanford.m
.......................\....\load_kdes_words.m
.......................\....\region_features_extra_rgbd.m
.......................\....\kdes_data
.......................\....\.........\rgbkdeswords_400_stanford.mat
.......................\....\.........\gkdes_params.mat
.......................\....\.........\lbpkdes_params.mat
.......................\....\.........\gkdeswords_400_stanford.mat
.......................\....\.........\gkdesdepth_params.mat
.......................\....\.........\rgbkdes_params.mat
.......................\....\.........\gkdeswords_200_fergus.mat
.......................\....\.........\spinkdes_params.mat
.......................\....\.........\rgbkdeswords_200_fergus.mat
.......................\....\.........\spinkdeswords_200_fergus.mat
.......................\....\.........\lbpkdeswords_400_stanford.mat
.......................\....\.........\gkdesdepthwords_200_fergus.mat
.......................\....\collect_superpixel_features_nyu_depth.m
.......................\....\classify_segmentation_tree.m
.......................\....\classify_superpixel.m
.......................\....\save_feature_rgbd.m
.......................\....\eval_superpixel_nyu_depth.m
.......................\....\get_kdes_weight_seg.m
.......................\....\visualize_label_stanford.m
.......................\....\DepthtoCloud.m
.......................\....\collect_tree_data.m
.......................\....\script_run_superpixel_labeling_stanford.m
.......................\....\save_feature_rgb.m
.......................\....\liblinear-weights-1.8-dense-float
.......................\....\.................................\linear.cpp
.......................\....\.................................\train
.......................\....\.................................\README.weight
.......................\....\.................................\predict.c
.......................\....\.................................\linear.o
.......................\....\.................................\COPYRIGHT
.......................\....\.................................\matlab
.......................\....\.................................\......\linear_model_matlab.c
.......................\....\.................................\.....