DocumentCode :
2290208
Title :
LabelMe video: Building a video database with human annotations
Author :
Yuen, Jenny ; Russell, Bryan ; Liu, Ce ; Torralba, Antonio
Author_Institution :
MIT, Cambridge, MA, USA
fYear :
2009
fDate :
Sept. 29 2009-Oct. 2 2009
Firstpage :
1451
Lastpage :
1458
Abstract :
Currently, video analysis algorithms suffer from lack of information regarding the objects present, their interactions, as well as from missing comprehensive annotated video databases for benchmarking. We designed an online and openly accessible video annotation system that allows anyone with a browser and internet access to efficiently annotate object category, shape, motion, and activity information in real-world videos. The annotations are also complemented with knowledge from static image databases to infer occlusion and depth information. Using this system, we have built a scalable video database composed of diverse video samples and paired with human-guided annotations. We complement this paper demonstrating potential uses of this database by studying motion statistics as well as cause-effect motion relationships between objects.
Keywords :
Internet; image motion analysis; image segmentation; object recognition; video databases; video signal processing; Internet; cause-effect motion relationships; diverse video samples; human-guided annotations; image databases; labelme video; motion statistics; real-world videos; video analysis algorithms; video annotation system; video database; Algorithm design and analysis; Computer vision; Humans; Image databases; Internet; Layout; Shape; Statistics; Tracking; Videoconference;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2009 IEEE 12th International Conference on
Conference_Location :
Kyoto
ISSN :
1550-5499
Print_ISBN :
978-1-4244-4420-5
Electronic_ISBN :
1550-5499
Type :
conf
DOI :
10.1109/ICCV.2009.5459289
Filename :
5459289
Link To Document :
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