Multimodal City-Identification on Flickr Videos Using Acoustic and Textual Features

We have performed city-verification of videos based on the videos' audio and metadata, using videos from the MediaEval Placing Task's video set, which contain consumerproduced videos “from-the-wild.” Eighteen cities were used as targets, for which acoustic and language models were trained, and against which test videos were scored. We have obtained the first known results for the city verification task, with an EER minimum of 21.8 percent. This result is well above-chance, even though the videos contain very few city-specific audio and metadata features. We have also demonstrated the complementarity of audio and metadata for this task.