Video Indexing, Search, Detection, and Description with Focus on TRECVID

There has been a tremendous growth in video data the last decade. People are using mobile phones and tablets to take, share or watch videos more than ever before. Video cameras are around us almost everywhere in the public domain (e.g. stores, streets, public facil- ities, ...etc). Efficient and effective retrieval methods are critically needed in different applications. The goal of TRECVID is to encour- age research in content-based video retrieval by providing large test collections, uniform scoring procedures, and a forum for orga- nizations interested in comparing their results. In this tutorial, we present and discuss some of the most important and fundamental content-based video retrieval problems such as recognizing prede- fined visual concepts, searching in videos for complex ad-hoc user queries, searching by image/video examples in a video dataset to retrieve specific objects, persons, or locations, detecting events, and finally bridging the gap between vision and language by looking into how can systems automatically describe videos in a natural language. A review of the state of the art, current challenges, and future directions along with pointers to useful resources will be presented by different regular TRECVID participating teams.