In this paper, we propose a new event recognition framework for consumer videos by leveraging a large amount of loosely labeled YouTube videos. Our work is based on the observation that a large amount of loosely labeled YouTube videos can be readily obtained by using keywords (also called tags) based search. However, the quality of YouTube videos is generally lower than con- sumer videos because YouTube videos are often down- sampled and compressed by the web server. In addition, YouTube videos may have been selected and edited to attract attention, while consumer videos are in their naturally captured state. In Fig. 1, we show four frames from two events (., “picnic” and.
