This report deals with the development of a computer vision system for
object tracking of everyday objects on a table using a head mounted
camera. The problem at hand is derived from the EU funded project
ARTHUR. A system must be developed which tracks objects with a
frame rate of at least 10 frames per second.
The system can in general be divided into 3 core parts; segmentation,
stabilization, and tracking.
The stabilization, which estimates the orientation of the camera
relative to the surroundings, utilizes window based correlation to
estimate the disparity between images and a 2D affine method to convert
the disparity to angles in world-space.
The segmentation of objects is solved by using a bipartite
approach. Initially pixels belonging to the table are found using
global thresholding in the hue channel of the HSV color model, and
subsequently pixels belonging to objects are found using the convex
The tracking part, is based on feature extraction of among
others invariant moments and histograms. Mahalanobis distance is used
for the feature matching, and feature prediction is based on simple
linear extrapolation. Furthermore, a general window based object
recognition method for handling occlusions is proposed which works on
histograms in the HSV color space.
The system is designed using Matlab, and a prototype is implemented in
C++ based on the Intel Corporation's Open Computer Vision Library
(OpenCV). The prototype contains the segmentation and tracking
component of the system. Occlusions are, however, not handled currently.
The test of the prototype showed that the system is capable of
tracking separate objects and is robust with respect to scaling and
rotations. Unique objects are tracked more robustly than objects with
similar color. The demand regarding a frame rate of 10 frames
per second has been tested and confirmed, as long as there are 6 or
fewer objects in the camera's field of view.
It is concluded that the system with the chosen delimitations works as
specified, but a number of future improvements is
suggested. Specifically stabilization and the method for handling
occlusions must be added to the current prototype in order to achieve