The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
CENTRIST: A Visual Descriptor for Scene Categorization
Abstract
CENsus TRansform hISTogram (CENTRIST), a new visual descriptor for recognizing topological places or scene categories, is introduced in this paper. We show that place and scene recognition, especially for indoor environments, require its visual descriptor to possess properties that are different from other vision domains (e.g., object recognition). CENTRIST satisfies these properties and suits the place and scene recognition task. It is a holistic representation and has strong generalizability for category recognition. CENTRIST mainly encodes the structural properties within an image and suppresses detailed textural information. Our experiments demonstrate that CENTRIST outperforms the current state of the art in several place and scene recognition data sets, compared with other descriptors such as SIFT and Gist. Besides, it is easy to implement and evaluates extremely fast.
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Robust Real-Time Face Detection
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A performance evaluation of local descriptors
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Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
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Metadata
- Authors
- Wu, J., & Rehg, J. M.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2011-08
- Volume
- 33
- Issue
- 8
- Pages
- 1489-1501
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2113855951
- Cited by
- 709
- References
- 40
- FWCI
- 49.39
- Type
- journal article
- Language
- en
- Open access
- closed
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