Smart video browsing with augmented navigation bars

Abstract

While accuracy and speed get a lot of attention in video retrieval research, the investigation of interactive retrieval tools gets less attention and is often regarded as trivial. We want to show that even simple ideas have potential to improve the retrieval performance by giving some automated support to the browsing user. We present a video browsing concept where video segments are clustered in several latent classes of similar content. The navigation bars of our video browser are augmented with different colors indicating where elements of these clusters are located. As humans are able to classify the content of clusters fast, they can benefit from this information when browsing a video. We present a study where we investigated how humans can be supported in different video browsing tasks with a color-based and a motion-based clustering of video content. © Springer-Verlag 2013.