3D Indoor Scenes Database

Swadzba A, Wachsmuth S (2009) : Bielefeld University. doi:10.4119/unibi/citec.2013.5.

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Abstract / Notes
This database was collected to explore spatial features for 3D indoor scene classification. It consists of sequences of 3D point clouds collected with a Swissranger. Each sequence shows a room of a certain room type. The data was collected while the camera was panned and tilted simulating a robot entering a room and looking around. The database is assembled from 28 sequences one sequence per specific room. A sequence is represented as set of text-files where the z-, x-, and y-values of one frame are stored row-wise in one file.
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Swadzba A, Wachsmuth S. (2009): 3D Indoor Scenes Database. Bielefeld University. doi:10.4119/unibi/citec.2013.5.
Swadzba, A., & Wachsmuth, S. (2009). 3D Indoor Scenes Database. Bielefeld University. doi:10.4119/unibi/citec.2013.5
Swadzba, A., and Wachsmuth, S. (2009). 3D Indoor Scenes Database. Bielefeld University. doi:10.4119/unibi/citec.2013.5.
Swadzba, A., & Wachsmuth, S., 2009. 3D Indoor Scenes Database. Bielefeld University. doi:10.4119/unibi/citec.2013.5
A. Swadzba and S. Wachsmuth, 3D Indoor Scenes Database. Bielefeld University, 2009. doi:10.4119/unibi/citec.2013.5.
Swadzba, A., Wachsmuth, S.: 3D Indoor Scenes Database. Bielefeld University (2009). doi:10.4119/unibi/citec.2013.5.
Swadzba, Agnes, and Wachsmuth, Sven. 3D Indoor Scenes Database. Bielefeld University, 2009. doi:10.4119/unibi/citec.2013.5
This data publication is cited in the following publications:
2034745
Indoor Scene Classification using combined 3D and Gist Features
Swadzba A, Wachsmuth S (2011)
In: Computer Vision - ACCV 2010. Lecture Notes in Computer Science, 6493. Berlin, Heidelberg: Springer: 201-215.
2563576
A Detailed Analysis of a New 3D Spatial Feature Vector for Indoor Scene Classification
Swadzba A, Wachsmuth S (2014)
Robotics and Autonomous Systems 62(5): 646-662.
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