| Dataset 7 LHI_SceneSegmentation_18 |
| Contents and Statistics : |
| Category |
Subcategory |
Number of Images |
Free |
Total |
| Outdoor(8) |
street |
15 |
11363 |
| seashore |
15 |
305 |
| rural |
15 |
57 |
| parking |
15 |
8452 |
| natrual landscape |
15 |
1360 |
| highway |
15 |
398 |
| harbor |
9 |
773 |
| cityview |
15 |
338 |
| Indoor(6) |
office |
15 |
765 |
| livingroom |
15 |
1389 |
| hall |
15 |
775 |
| corridor |
15 |
240 |
| bedroom |
15 |
9816 |
| bathroom |
15 |
1870 |
| Activity(4) |
sports |
15 |
844 |
| Shop |
15 |
299 |
| meeting |
15 |
229 |
| lecture |
15 |
572 |
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Matlab codes to load this category (see MatlabToolbox page for more information):
clear; close all;
HOMEIMAGES = 'C:\Yourdatabase\LHI_SceneSegmentation_20\Images';
HOMEANNOTATIONS = 'C:\Yourdatabase\LHI_SceneSegmentation_20\Annotations';
HOMELABELMAPS = 'C:\Yourdatabase\LHI_SceneSegmentation_20\LabelMaps';
Code to load the database and mapping the names
rawDB = LHIdatabase(HOMEANNOTATIONS); NEWHOMELABELMAPS = 'C:/temp/yourposition/';D=LHIregulatenames(rawDB,HOMELABELMAPS,NEWHOMELABELMAPS,'Sport_names.txt'); |
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Code to produce the figure below:
LHIobjectnames(D);
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Figure 1 Object frequency count |
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View one image for hierarchical decomposition
Code to produce the figure:
LHIdbshowscenes(D(ind),HOMEIMAGES);
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Figure 2. Hierarchical decomposition of an image |
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Statistics of the category
General statistics including number of keypoints on the boundary for each object, sum of object/image area ratio. Position (x,y axis of center point) histogram.
Code to produce figure:
[objectnames, instancecounts, areacounts, pointcounts, positions]=LHIobjectstats(D, HOMEIMAGES, NEWHOMELABELMAPS); |
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Figure 3 Histogram of the number of key points used to define each object |
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Figure 4. Histogram of the percentage of pixels occupied (relative to the image size) by each object instance |
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Figure 5. This plot shows the distribution of locations occupied by each instance. Each dot corresponds to the original location, relative to the image frame, of each object instance. These plots help to understand some of the biases that the photographers might have when taking pictures of specific objects. |
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