  Millions of surveillance cameras operate at 24x7 generating huge amount of
visual data for processing. However, retrieval of important activities from
such a large data can be time consuming. Thus, researchers are working on
finding solutions to present hours of visual data in a compressed, but
meaningful way. Video synopsis is one of the ways to represent activities using
relatively shorter duration clips. So far, two main approaches have been used
by researchers to address this problem, namely synopsis by tracking moving
objects and synopsis by clustering moving objects. Synopses outputs, mainly
depend on tracking, segmenting, and shifting of moving objects temporally as
well as spatially. In many situations, tracking fails, thus produces multiple
trajectories of the same object. Due to this, the object may appear and
disappear multiple times within the same synopsis output, which is misleading.
This also leads to discontinuity and often can be confusing to the viewer of
the synopsis. In this paper, we present a new approach for generating
compressed video synopsis by grouping tracklets of moving objects. Grouping
helps to generate a synopsis where chronologically related objects appear
together with meaningful spatio-temporal relation. Our proposed method produces
continuous, but a less confusing synopses when tested on publicly available
dataset videos as well as in-house dataset videos.
