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ACCV
2010
Springer
12 years 11 months ago
Indoor Scene Classification Using Combined 3D and Gist Features
Abstract. Scene categorization is an important mechanism for providing high-level context which can guide methods for a more detailed analysis of scenes. State-of-the-art technique...
Agnes Swadzba, Sven Wachsmuth
ICCV
2011
IEEE
12 years 4 months ago
Manhattan Scene Understanding Using Monocular, Stereo, and 3D Features
This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through struct...
Alex Flint, David Murray, Ian Reid
GFKL
2007
Springer
202views Data Mining» more  GFKL 2007»
13 years 8 months ago
Collective Classification for Labeling of Places and Objects in 2D and 3D Range Data
In this paper, we present an algorithm to identify types of places and objects from 2D and 3D laser range data obtained in indoor environments. Our approach is a combination of a c...
Rudolph Triebel, Óscar Martínez Mozo...
CVPR
2005
IEEE
14 years 6 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...
CVPR
2009
IEEE
14 years 11 months ago
Holistic Context Modeling using Semantic Co-occurrences
We present a simple framework to model contextual relationships between visual concepts. The new framework combines ideas from previous object-centric methods (which model conte...
Nikhil Rasiwasia (University Of California, San Di...