Generating “Visual Clouds” from Multiplex Networks for TV News Archive Query Visualization
Haolin Ren, Benjamin Renoust, Marie-Luce Viaud, Guy Mélançon, Shin’ichi Satoh · 2018
Advances in multimedia analysis, enables access and indexing of huge and rich video content. However, delivering this heterogeneous content remains a challenge. We proposes the use of multiplex networks to combine both textual and visual semantic cues extracted from TV news videos for interactive search refinement on heterogeneous data. After preprocessing, the indexed videos can be queried, for which result space is summarized in a visual cloud helping query refinement with contextual information by combining visual and textual cues. We leverage on properties of multiplex networks to extract a hierarchy of layers, which not only contextualizes results, but also guides the construction of our visual cloud, and its interactions.