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This paper presents a FAST Corner Detection object scanning to improve SLAM technique, which is SLAM, has a weakness in extracting features in the real-world object. The use of User Defined Target and Extended Tracking are for making this work more convenient and reliable. We can trace the object even though the object does not exist, so this improves the function of markerless itself. The use of Raycast is for the make labeling the objects or features in the scanned object. In this research, we executed multivarious intensity to test the FAST Corner Detection to increase function in real world feature extraction and prove it better than SLAM. Then, we got the result where is a brighter condition will get faster recognition. The best environments for augmentation are in the range of 80-190, they took in less than 1 second. On the contrary, the intensity outside of the range such as ≤50 or ≥200, has a deficiency of augmentation. The range of ≤50, there was no augmentation cause of low intensity. For the range of ≥200, we haven’t made measurements as we don’t have the resources yet, but we hypothesize that the object would be corrupt or we may call it was overexposure cause of the intensity is too high. So, this could also lead to augmentation will not occur.

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