Unsupervised Detection of Video Sub-scenes

George I. Kamberov, Matt Burlick, Lazaros Karydas, Olga Koteoglou

Abstract: The analysis of videos taken by active operators recording human interactions and activities in the field presents a new set of challenges. For brevity in this paper we will call such subject centric field grade videos ad hoc videos of events. Human test subjects readily segment ad hoc videos of events into scene-like segments. These segmentations can not be replicated by the state of the art automatic video segmentation algorithms. We propose and evaluate a method to segment ad hoc videos of events into atomic semantics units. Motivated by [Bel74] we call these units sub-scenes. Our experiments show that the segments detected by human subjects are sequences of sub-scenes. Thus the sub-scenes appear to be a semantic version of the video shots that are used to piece together scenes by state of the art video segmentation algorithms.

External IDs:dblp:conf/icpr/KamberovBKK14