Scene Image Recognition with Multi Level Resolution Semantic Modeling
In this paper, we propose a multi-level resolution semantic modeling for automatic scene recognition. The basic idea of the semantic modeling is to classify local image regions into semantic concept classes such as water, sunset, or sky, and use occurrence frequency of local regions semantic concepts for global image representation 1. However, how to decide size of the local image regions is a trial problem. The optimized region size would be dynamically changing for different scene or concept types.Therefore, this paper proposed a dynamical region size (Multi-level resolution) of local image regions for semantic concept model, and fusion the probabilities to scene types of several resolutions for final recognition of a scene image. Experimental results show that the recognition rate using our proposed algorithm is much better than that using the conventional semantic modeling method for scene recognition.
Semantic Modeling multi level resolution scene recognition
Yoshiyuki Tanaka Atsushi Okamoto Xian-Hua Han Yen-Wei Chen Xiang Ruan
Department of Science and Engineering Ritsumeian University Graduate School Kusatsu, Japan OMRON Corporation Japan
国际会议
成都
英文
612-615
2010-06-23（万方平台首次上网日期，不代表论文的发表时间）