Abstract:
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As early stage of video processing, we introduce an iter-
ative trajectory merging algorithm that produces a region-
based and hierarchical representation of the video se-
quence, called the Trajectory Binary Partition Tree (BPT).
From this representation, many analysis and graph cut tech-
niques can be used to extract partitions or objects that are
useful in the context of specific applications.
In order to define trajectories and to create a precise
merging algorithm, color and motion cues have to be used.
Both types of informations are very useful to characterize
objects but present strong differences of behavior in the spa-
tial and the temporal dimensions. On the one hand, scenes
and objects are rich in their spatial color distributions, but
these distributions are rather stable over time. Object mo-
tion, on the other hand, presents simple structures and low
spatial variability but may change from frame to frame. The
proposed algorithm takes into account this key difference
and relies on different models and associated metrics to
deal with color and motion information. We show that the
proposed algorithm outperforms existing hierarchical video
segmentation algorithms and provides more stable and pre-
cise regions |