Labeled dataset for integral evaluation of moving object detection algorithms: LASIESTA
•Complete database for assessing the quality of foreground detection strategies.•Indoor and outdoor sequences with many categories addressing different challenges.•All the sequences are fully annotated at both pixel and object levels.•Information concerning stationary foreground objects.•Sequences r...
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| Published in: | Computer vision and image understanding Vol. 152; pp. 103 - 117 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Inc
01.11.2016
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| Subjects: | |
| ISSN: | 1077-3142, 1090-235X |
| Online Access: | Get full text |
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| Abstract | •Complete database for assessing the quality of foreground detection strategies.•Indoor and outdoor sequences with many categories addressing different challenges.•All the sequences are fully annotated at both pixel and object levels.•Information concerning stationary foreground objects.•Sequences recorded with static and moving cameras.
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A public, complete, compact, and well structured database is proposed, which allows to test moving object detection strategies. The database is composed of many real indoor and outdoor sequences organized in different categories, each of one covering a specific challenge. In contrast to other databases, the proposed one is fully annotated at both pixel and object levels. Therefore, it is suitable for strategies exclusively focused on the detection of moving objects and also for those that integrate tracking algorithms in their detection approaches. Additionally, it contains sequences recorded with static and moving cameras and it also provides information about the moving objects remaining temporally static.
To test its usefulness, the database has been used to assess the quality of some outstanding moving object detection methods. |
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| AbstractList | •Complete database for assessing the quality of foreground detection strategies.•Indoor and outdoor sequences with many categories addressing different challenges.•All the sequences are fully annotated at both pixel and object levels.•Information concerning stationary foreground objects.•Sequences recorded with static and moving cameras.
[Display omitted]
A public, complete, compact, and well structured database is proposed, which allows to test moving object detection strategies. The database is composed of many real indoor and outdoor sequences organized in different categories, each of one covering a specific challenge. In contrast to other databases, the proposed one is fully annotated at both pixel and object levels. Therefore, it is suitable for strategies exclusively focused on the detection of moving objects and also for those that integrate tracking algorithms in their detection approaches. Additionally, it contains sequences recorded with static and moving cameras and it also provides information about the moving objects remaining temporally static.
To test its usefulness, the database has been used to assess the quality of some outstanding moving object detection methods. |
| Author | García, Narciso Cuevas, Carlos Yáñez, Eva María |
| Author_xml | – sequence: 1 givenname: Carlos surname: Cuevas fullname: Cuevas, Carlos email: ccr@gti.ssr.upm.es – sequence: 2 givenname: Eva María surname: Yáñez fullname: Yáñez, Eva María email: eyg@gti.ssr.upm.es – sequence: 3 givenname: Narciso surname: García fullname: García, Narciso email: narciso@gti.ssr.upm.es |
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| Keywords | Background subtraction Dataset Challenges Foreground detection Database Ground-truth Moving camera Moving object detection Stationary foreground |
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