LabelMe: Online Image Annotation and Applications

Central to the development of computer vision systems is the collection and use of annotated images spanning our visual world. Annotations may include information about the identity, spatial extent, and viewpoint of the objects present in a depicted scene. Such a database is useful for the training...

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Vydáno v:Proceedings of the IEEE Ročník 98; číslo 8; s. 1467 - 1484
Hlavní autoři: Torralba, Antonio, Russell, Bryan C., Yuen, Jenny
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.08.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
3-D
Annotations
Application software
Computer graphics
Computer vision
Data mining
Image database
Image databases
image statistics
Internet
Layout
object detection
object recognition
On-line systems
Online
online annotation tool
Spatial databases
Statistics
video annotation
Vision systems
Visual databases
ISSN:0018-9219, 1558-2256
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Popis
Shrnutí:Central to the development of computer vision systems is the collection and use of annotated images spanning our visual world. Annotations may include information about the identity, spatial extent, and viewpoint of the objects present in a depicted scene. Such a database is useful for the training and evaluation of computer vision systems. Motivated by the availability of images on the Internet, we introduced a web-based annotation tool that allows online users to label objects and their spatial extent in images. To date, we have collected over 400 000 annotations that span a variety of different scene and object classes. In this paper, we show the contents of the database, its growth over time, and statistics of its usage. In addition, we explore and survey applications of the database in the areas of computer vision and computer graphics. Particularly, we show how to extract the real-world 3-D coordinates of images in a variety of scenes using only the user-provided object annotations. The output 3-D information is comparable to the quality produced by a laser range scanner. We also characterize the space of the images in the database by analyzing 1) statistics of the co-occurrence of large objects in the images and 2) the spatial layout of the labeled images.
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ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2010.2050290