The majority of visual SLAM techniques utilize interest points as
landmarks. Therefore, they suffer from two main problems; scalability and data
association reliability. Recently, there has been increasing interest in using
higher level object description to reduce the number of tracked features and
improve the data association among frames. In this paper, a simple visual mono
SLAM algorithm is presented utilizing objects as landmarks and uses fast
template matching to track predefined templates of these objects in an indoor
environment. The results are described for real experiments with an indoor
mobile robot platform. The performance of the proposed technique is evaluated
and compared to recent methods.