Return to search

Contextual Priming for Object Detection

There is general consensus that context can be a rich source of information about an object's identity, location and scale. In fact, the structure of many real-world scenes is governed by strong configurational rules akin to those that apply to a single object. Here we introduce a simple probabilistic framework for modeling the relationship between context and object properties based on the correlation between the statistics of low-level features across the entire scene and the objects that it contains. The resulting scheme serves as an effective procedure for object priming, context driven focus of attention and automatic scale-selection on real-world scenes.

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/7239
Date01 September 2001
CreatorsTorralba, Antonio, Sinha, Pawan
Source SetsM.I.T. Theses and Dissertation
Languageen_US
Detected LanguageEnglish
Format27 p., 40187890 bytes, 5238575 bytes, application/postscript, application/pdf
RelationAIM-2001-020, CBCL-205

Page generated in 0.0018 seconds