Electrical and Electronic Engineering, Imperial College London
Doi
Abstract
There have been significant advances in the computer vision field during the last decade.
During this period, many methods have been developed that have been successful in solving
challenging problems including Face Detection, Object Recognition and 3D Scene Reconstruction.
The solutions developed by computer vision researchers have been widely
adopted and used in many real-life applications such as those faced in the medical and
security industry. Among the different branches of computer vision, Object Recognition
has been an area that has advanced rapidly in recent years. The successful introduction of
approaches such as feature extraction and description has been an important factor in the
growth of this area. In recent years, researchers have attempted to use these approaches
and apply them to other problems such as Content Based Image Retrieval and Tracking.
In this work, we present a novel system that finds correspondences between people seen in
different images. Unlike other approaches that rely on a video stream to track the movement
of people between images, here we present a feature-based approach where we locate a
target’s new location in an image, based only on its visual appearance.
Our proposed system comprises three steps. In the first step, a set of features is extracted
from the target’s appearance. A novel algorithm is developed that allows extraction of features
from a target that is particularly suitable to the modelling task. In the second step,
each feature is characterised using a combined colour and texture descriptor. Inclusion
of information relating to both colour and texture of a feature add to the descriptor’s distinctiveness.
Finally, the target’s appearance and pose is modelled as a collection of such
features and descriptors. This collection is then used as a template that allows us to search
for a similar combination of features in other images that correspond to the target’s new
location.
We have demonstrated the effectiveness of our system in locating a target’s new position in
an image, despite differences in viewpoint, scale or elapsed time between the images. The
characterisation of a target as a collection of features also allows our system to robustly
deal with the partial occlusion of the target
