Visual graph modeling for scene recognition and mobile robot localization
Image retrieval and categorization may need to consider several types of visual features and spatial information between them (e.g., different point of views of an image). This paper presents a novel approach that exploits an extension of the language modeling approach from information retrieval to...
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| Veröffentlicht in: | Multimedia tools and applications 2012-09, Vol.60 (2), p.419-441 |
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| container_title | Multimedia tools and applications |
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| creator | Pham, Trong-Ton Mulhem, Philippe Maisonnasse, Loïc Gaussier, Eric Lim, Joo-Hwee |
| description | Image retrieval and categorization may need to consider several types of visual features and spatial information between them (e.g., different point of views of an image). This paper presents a novel approach that exploits an extension of the language modeling approach from information retrieval to the problem of graph-based image retrieval and categorization. Such versatile graph model is needed to represent the multiple points of views of images. A language model is defined on such graphs to handle a fast graph matching. We present the experiments achieved with several instances of the proposed model on two collections of images: one composed of 3,849 touristic images and another composed of 3,633 images captured by a mobile robot. Experimental results show that using visual graph model (VGM) improves the accuracies of the results of the standard language model (LM) and outperforms the Support Vector Machine (SVM) method. |
| doi_str_mv | 10.1007/s11042-010-0598-8 |
| format | Article |
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| subjects | Artificial Intelligence Computer Communication Networks Computer Science Data Structures and Information Theory Graphs Information Retrieval Machine Learning Multimedia Multimedia Information Systems Retrieval Robots Special Purpose and Application-Based Systems Support vector machines Visual |
| title | Visual graph modeling for scene recognition and mobile robot localization |
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