Integrated content and context analysis for mobile landmark recognition

This paper proposes a new approach for mobile landmark recognition based on integrated content and context analysis. Conventional scene/landmark recognition methods focus mainly on nonmobile desktop/PC platform, where content analysis alone is used to perform landmark recognition. These nonmobile systems, however, do not take unique features of mobile devices into consideration, e.g., limited computational power and fast response time requirement of mobile users. On the contrary, most existing context-aware content mobile landmark recognition methods mainly rely on global positioning system location information for context analysis. In view of this, this paper proposes an effective method that employs an integration of content and context analysis to perform landmark recognition using mobile devices. A new bags-of-words (BoW) framework is developed to perform content analysis. It is then integrated with context analysis involving fusion of location and direction information to perform mobile landmark recognition. Experimental results based on the NTU50Landmark database show that the proposed method can achieve good recognition performance in mobile landmark recognition.