In this paper, we present a new framework of video object
segmentation, in which we formulate the task of extracting
prominent objects from a scene as the problem of hypergraph
cut. We initially over-segment each frame in the sequence,
and take the over-segmented image patches as the
vertices in the graph. Different from the traditional pairwise
graph structure, we build a novel graph structure, hypergraph,
to represent the complex spatio-temporal neighborhood
relationship among the patches. We assign each
patch with several attributes that are computed from the
optical flow and the appearance-based motion profile, and
the vertices with the same attribute value is connected by a
hyperedge. Through all the hyperedges, not only the complex
non-pairwise relationships between the patches are described,
but also their merits are integrated together organically.
The task of video object segmentation is equivalent
to the hypergraph partition, which can be solved by the hypergr...
Dimitris N. Metaxas, Qingshan Liu, Yuchi Huang