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.