AUTOMATIC DAMAGE RECOVERY OF OLD PHOTOS IN PAINTING AND RESTORATION

In recent years, motion detection has attracted a great interest from
computer vision researchers due to its promising applications in many areas, such as
video surveillance. In motion detection the task is to detect a region of interest
embodied in a region of awareness, where the region of awareness, or in terms of the
camera geometry, the field of view, is defined as the portion of environment being
monitored. The region of interest is in the present case the portion of the environment
with activity. For the sake of simplicity and generality, recognition-based detection is
not assumed. A region of interest can be therefore a person, an animal, or an artifact;
circumscribed with the term moving objects. The motion detection algorithm is based
on background change detection, i.e. the difference method by background
subtraction. This assumes that the background model for the expected image sequence
is known in advance and that it does not change over time. Such conditions are rarely
given for an indoor scene, e.g. when illumination changes occur and objects are
moved around. Hence a confident adaption method is required. An adaption region
must be specified that discerns between foreground and background objects. By
definition the background change detection itself yields that distinction but is
inappropriate because undetected foreground objects will be falsely adapted to the
modelled background image.