文件名称:scene_labeling_cvpr2012_v1

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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
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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

.......................\....\.................................\.....

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