AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGES
Recently automatic detection of people crowds from images became a very important research field, since it can provide crucial information especially for police departments and crisis management teams. Due to the importance of the topic, many researchers tried to solve this problem using street came...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2013-04-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-3-W22/221/2011/isprsarchives-XXXVIII-3-W22-221-2011.pdf |
| _version_ | 1819057389725286400 |
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| author | B. Sirmacek P. Reinartz |
| author_facet | B. Sirmacek P. Reinartz |
| author_sort | B. Sirmacek |
| collection | DOAJ |
| description | Recently automatic detection of people crowds from images became a very important research field, since it can provide crucial
information especially for police departments and crisis management teams. Due to the importance of the topic, many researchers tried
to solve this problem using street cameras. However, these cameras cannot be used to monitor very large outdoor public events. In order
to bring a solution to the problem, herein we propose a novel approach to detect crowds automatically from remotely sensed images,
and especially from very high resolution satellite images. To do so, we use a local feature based probabilistic framework. We extract
local features from color components of the input image. In order to eliminate redundant local features coming from other objects in
given scene, we apply a feature selection method. For feature selection purposes, we benefit from three different type of information;
digital elevation model (DEM) of the region which is automatically generated using stereo satellite images, possible street segment
which is obtained by segmentation, and shadow information. After eliminating redundant local features, remaining features are used
to detect individual persons. Those local feature coordinates are also assumed as observations of the probability density function (pdf)
of the crowds to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding pdf which gives us
information about dense crowd and people locations. We test our algorithm usingWorldview-2 satellite images over Cairo and Munich
cities. Besides, we also provide test results on airborne images for comparison of the detection accuracy. Our experimental results
indicate the possible usage of the proposed approach in real-life mass events. |
| first_indexed | 2024-12-21T13:38:32Z |
| format | Article |
| id | doaj.art-b5a2c4f878314770b9101459ab0b6f1f |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-21T13:38:32Z |
| publishDate | 2013-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-b5a2c4f878314770b9101459ab0b6f1f2022-12-21T19:02:05ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342013-04-01XXXVIII-3/W2222122610.5194/isprsarchives-XXXVIII-3-W22-221-2011AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGESB. Sirmacek0P. Reinartz1German Aerospace Center (DLR), Remote Sensing Technology Institute P.O. Box 1116, 82230, Wessling, GermanyGerman Aerospace Center (DLR), Remote Sensing Technology Institute P.O. Box 1116, 82230, Wessling, GermanyRecently automatic detection of people crowds from images became a very important research field, since it can provide crucial information especially for police departments and crisis management teams. Due to the importance of the topic, many researchers tried to solve this problem using street cameras. However, these cameras cannot be used to monitor very large outdoor public events. In order to bring a solution to the problem, herein we propose a novel approach to detect crowds automatically from remotely sensed images, and especially from very high resolution satellite images. To do so, we use a local feature based probabilistic framework. We extract local features from color components of the input image. In order to eliminate redundant local features coming from other objects in given scene, we apply a feature selection method. For feature selection purposes, we benefit from three different type of information; digital elevation model (DEM) of the region which is automatically generated using stereo satellite images, possible street segment which is obtained by segmentation, and shadow information. After eliminating redundant local features, remaining features are used to detect individual persons. Those local feature coordinates are also assumed as observations of the probability density function (pdf) of the crowds to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding pdf which gives us information about dense crowd and people locations. We test our algorithm usingWorldview-2 satellite images over Cairo and Munich cities. Besides, we also provide test results on airborne images for comparison of the detection accuracy. Our experimental results indicate the possible usage of the proposed approach in real-life mass events.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-3-W22/221/2011/isprsarchives-XXXVIII-3-W22-221-2011.pdf |
| spellingShingle | B. Sirmacek P. Reinartz AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGES The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGES |
| title_full | AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGES |
| title_fullStr | AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGES |
| title_full_unstemmed | AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGES |
| title_short | AUTOMATIC CROWD ANALYSIS FROM VERY HIGH RESOLUTION SATELLITE IMAGES |
| title_sort | automatic crowd analysis from very high resolution satellite images |
| url | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-3-W22/221/2011/isprsarchives-XXXVIII-3-W22-221-2011.pdf |
| work_keys_str_mv | AT bsirmacek automaticcrowdanalysisfromveryhighresolutionsatelliteimages AT preinartz automaticcrowdanalysisfromveryhighresolutionsatelliteimages |