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Spring Lattice Counting Grids: Scene Recognition Using Deformable Positional Constraints
- Source :
- Computer Vision – ECCV 2012 ISBN: 9783642337826, ECCV (6)
- Publication Year :
- 2012
- Publisher :
- Springer Berlin Heidelberg, 2012.
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Abstract
- Adopting the Counting Grid (CG) representation [1], the Spring Lattice Counting Grid (SLCG) model uses a grid of feature counts to capture the spatial layout that a variety of images tend to follow. The images are mapped to the counting grid with their features rearranged so as to strike a balance between the mapping quality and the extent of the necessary rearrangement. In particular, the feature sets originating from different image sectors are mapped to different sub-windows in the counting grid in a configuration that is close, but not exactly the same as the configuration of the source sectors. The distribution over deformations of the sector configuration is learnable using a new spring lattice model, while the rearrangement of features within a sector is unconstrained. As a result, the CG model gains a more appropriate level of invariance to realistic image transformations like view point changes, rotations or scales. We tested SLCG on standard scene recognition datasets and on a dataset collected with a wearable camera which recorded the wearer's visual input over three weeks. Our algorithm is capable of correctly classifying the visited locations more than 80% of the time, outperforming previous approaches to visual location recognition. At this level of performance, a variety of real-world applications of wearable cameras become feasible.
Details
- ISBN :
- 978-3-642-33782-6
- ISBNs :
- 9783642337826
- Database :
- OpenAIRE
- Journal :
- Computer Vision – ECCV 2012 ISBN: 9783642337826, ECCV (6)
- Accession number :
- edsair.doi...........090be4883c27dd1e31ca341bc2852beb