Integrating Low-Level and Semantic Visual Cues for Improved Image-to-Video Experiences

Nowadays, the heterogeneity of networks, terminals, and users is growing. At the same time, the availability and usage of multimedia content is increasing, which has raised the relevance of content adaptation technologies able to fulfill the needs associated to all usage conditions. For example, mobile displays tend to be too small to allow one to see all the details of an image. This paper presents an innovative method to integrate low-level and semantic visual cues into a unique visual attention map that represents the most interesting contents of an image, allowing the creation of a video sequence that browses through the image displaying its regions of interest in detail. The architecture of the developed adaptation system, the processing solutions and also the principles and reasoning behind the algorithms that have been developed and implemented are presented in this paper. Special emphasis is given to the integration of low-level and semantic visual cues for the maximization of the image to video adapted experience.