Image Analysis for Video Surveillance Based Traffic Monitoring System
Mr. Rahane Wasudeo P.; Mr. H. K. Sawant
Visual analysis is concerned with detection and
analysis of a target object in a sequential stream of images.
While many algorithms are successful to detect objects
effectively in controlled environments, they get bugged with
the variations of the object’s appearance or with the
surrounding change. It happens as the existing algorithms
employ fixed appearance surroundings for the objects. Such
systems are trained using appearance of the data available
before the surveillance begins, which limits the range of
modeling, and ignores a large area of information (eg: shape
change or lighting conditions) which becomes dynamically
effective during surveillance. Traffic-video- surveillance
system that incrementally learns a subspace representation,
with accordance to the changes in the appearance of the
target. The proposed system is decomposed into two
independent sub-problems. The first problem is to detect
foreground objects on a frame-by-frame basis. It is done by
labeling each concerned pixel in the image frame as object
foreground or object background. The second is the coupling
of object observations at different points in an inter-related
sequence to extract the moving object's trajectory.