Release Time:2019-03-11  Hits:

Indexed by: Conference Paper

Date of Publication: 2010-08-07

Included Journals: Scopus、EI

Page Number: 75-78

Abstract: The contributions of image blocks to the holistic scene semantic classification are further exploited in this paper. An image is subdivided into non-overlapping regular grid of blocks hierarchically, 2x2 blocks at the first level and 3x3 blocks at the second level. For each level, "bag-of- features" strategy is deployed to predict the scene category of each block. Then the holistic scene category of an image can be recognized through a vote model based on the semantic categories of blocks at all levels in this image. Classification performance is compared to five state of the art approaches using their own datasets and testing protocols. In all cases, the proposed model achieves equal or superior results. Source codes are available by email. ? 2010 IEEE.