Object or background: Whose call is it in complicated scene classification?

Lichao Mou, Xiaoqiang Lu, Yuan Yuan

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Scene semantic parsing is a challenging problem in the field of computer vision. Most approaches exploit low-level features to describe the whole scene. However, there is a large semantic gap between low-level features and high-level scene semantic. In this paper, a scene classification approach is proposed by exploiting semantic objects/materials of the background to reduce the semantic gap. The proposed approach can be divided three steps: First we construct two high-level semantic features (BCFs and BSLFs). Second, we design an approach to learn the prior probability of the Bayesian Networks from these two semantic features of training images. Finally, Bayesian Networks is used to achieve the goal of scene classification. Experimental results show that our approach achieves state-of-the-art performance on the task of scene classification compare with other approaches.

源语言英语
主期刊名2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings
543-546
页数4
DOI
出版状态已出版 - 2013
已对外发布
活动2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Beijing, 中国
期限: 6 7月 201310 7月 2013

出版系列

姓名2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings

会议

会议2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013
国家/地区中国
Beijing
时期6/07/1310/07/13

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