Emotional Analysis and Annotation of Tourism Landscape Images Based on Tourist Experience

Tourist attractions need to optimize and upgrade their tourist services and tourist experience, according to the trendy topics on the Internet and the we media. This calls for objective evaluation of tourist experience, and accurately depiction of tourist emotions upon looking at tourism landscape images (TLIs). However, most of the existing methods for image emotional analysis cannot overcome the semantic gap, or handle an extraordinarily large image set. To solve the problems, this paper implements emotional analysis and annotation of TLIs based on tourist experience Firstly, the flow of tourist experience evaluation was expounded, and a model was constructed to evaluate tourist experience. Next, the forms of feature-based semantic information were specified for TLIs, and the emotional features were calculated for such images. After that, a semantic selection model was established to generate the emotional feature subsets of TLIs. Finally, the proposed model was verified through experiments on image emotional classification and annotation, and the relevant results were analyzed in details.