Video annotations of Mexican nature in a collaborative environment

Multimedia content production and storage in repositories are now an increasingly widespread practice. Indexing concepts for search in multimedia libraries are very useful for users of the repositories. However the search tools of content-based retrieval and automatic video tagging, still do not have great consistency. Regardless of how these systems are implemented, it is of vital importance to possess lots of videos that have concepts tagged with ground truth (training and testing sets). This paper describes a novel methodology to make complex annotations on video resources through ELAN software. The concepts are annotated and related to Mexican nature in a High Level Features (HLF) from development set of TRECVID 2014 in a collaborative environment. Based on this set, each nature concept observed is tagged on each video shot using concepts of the TRECVid 2014 dataset. We also propose new concepts,-like tropical settings, urban scenes, actions, events, weather, places for name a few. We also propose specific concepts that best describe video content of Mexican culture. We have been careful to get the database tagged with concepts of nature and ground truth. It is evident that a collaborative environment is more suitable for annotation of concepts related to ground truth and nature. As a result a Mexican nature database was built. It also is the basis for testing and training sets to automatically classify new multimedia content of Mexican nature.