New Object Bank Method for Scene Classification Based on GBVS

doi:10.3969/j.issn.1006-2475.2017.01.012

Abstract

Abstract: Object bank (OB) representation is a novel image representation for high-level visual tasks, which encodes semantic and spatial information of the objects within an image. However, the poor precision of the object detectors in OB method influences the extraction effect of high-level image feature. In order to solve this problem, a new OB method improved by Graph-Based Visual Saliency (GBVS) is proposed. Firstly, GBVS saliency model is utilized to process the image and detect the saliency regions and extract better high-level feature. The experiments results show that the proposed method performs better in classification and increases the classification accuracy of 4%.

Key words: object bank, GBVS, scene classification, visual saliency, high-level feature

CLC Number:

TP751

CHEN Meng-ting1, CHEN Si-xi2. New Object Bank Method for Scene Classification Based on GBVS[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.01.012.

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