  SLAM is a very popular research stream in computer vision and robotics
nowadays. For more effective SLAM implementation it is necessary to have
reliable informa- tion about the environment, also the data should be aligned
and scaled according to the real world coordinate system. Monocular SLAM
research is an attractive sub-stream, because of the low equipment cost, size
and weight. In this paper we present a way to build a conversion from LSD-SLAM
coordinate space to the real world coordinates using a true metric scale with
IMU sensor data implementation. The causes of differences between the real and
calculated spaces are explained and the possibility of conversions between the
spaces is proved. Additionally, a closed-form solution for inter space trans-
formation calculation is presented. The synthetic method of generating high
level accurate and well controlled input data for the LSD-SLAM algorithm is
presented. Finally, the reconstructed 3D environment representation is
delivered as an output of the implemented conversion.
