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This paper proposes a new information fusion approach that employs two information components for mobile landmark recognition, which includes: content analysis and context analysis. Existing landmark recognition works are mainly based on PC platform, which uses content analysis alone for recognition, and thus has a large computation cost and cannot satisfy mobile users' fast response time requirements...
This paper proposes a discriminative learning bags-of-words (BoW) approach for mobile landmark recognition at patch and image levels. Conventional methods often treat the local patches and images equally important for recognition and do not differentiate their different importance. Although there exist several works that consider the patches' discrimination information, they mainly focus on which...
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...
The growing usage of mobile camera phones has led to proliferation of many mobile applications. Landmark recognition is one of the mobile applications that are gaining more attention in recent years. The main idea of the application is that a user will use a camera phone to capture the image of a landmark or building and then the system will analyze, identify, and inform the user the name of the captured...
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