Abstract

This paper presents an improved frame-to-frame (F-2-F) compressed
video matching technique based on local features extracted from reduced size
images, in contrast with previous F-2-F techniques that utilized global fea-
tures extracted from full size frames. The revised technique addresses both
accuracy and computational cost issues of the traditional F-2-F approach. Ac-
curacy is improved through using local features, while computational cost issue
is addressed through extracting those local features from reduced size images.
For compressed videos, the DC-image sequence, without full decompression, is
used. Utilizing such small size images (DC-images) as a base for the proposed
work is important, as it pushes the traditional F-2-F from o�-line to real-time
operational mode. The proposed technique involves addressing an important
problem: namely the extraction of enough local features from such a small size
images to achieve robust matching. The relevant arguments and supporting
evidences for the proposed technique are presented. Experimental results and
evaluation, on multiple challenging datasets, show considerable computational
time improvements for the proposed technique accompanied by a comparable
or higher accuracy than state-of-the-art related techniques.