Spatial design and information visualization of dynamic graphics in the interactive environment of digital media

In this study, the spatial design and information visualization of dynamic graphics is examined on the basis of the interactive environment of digital media. The conventional Bag of Visual Words model (BoVW) uses only the image feature domain and neglects the contextual semantic information of the image design. This study proposes an image scene visualization algorithm based on the contextual semantic information. First, on the basis of the conventional BoVW, we introduce the Markov random field model to model the image contextual semantic information. Second, we use a density-based adaptive selection method to choose the number of the optimal probabilistic latent semantic analysis model. Finally, we use the support vector machine to perform scene visualization. Experimental results show that based on the conventional BoVW model, our algorithm can effectively utilize the contextual semantic information of images and improve the performance of the spatial design and information visualization of dynamic graphics in the interactive environment of digital media.