# A Novel Method Using 3D Interest Points to Place Markers on a Large Object in Augmented Reality
## 4 Conclusions  
This paper proposed a multiple marker placement method to minimize the inevitable problems when placing markers in AR and validated its performance. The difference between the proposed and conventional methods is that, unlike the conventional method that randomly positions the markers, the proposed method automatically determines the marker positions by reflecting the geometric features of the virtual object. The proposed method calculates the CSA and DoI within the segmented area by dividing the virtual object as evenly as possible and using the interest points. To consider all of these, the MPS score formula based on the weighted mean was derived, and the scores for all faces were calculated. The positions of multiple markers were determined at the center of the face with the highest MPS score in each segmented area. In the proposed method, the weight for calculating the MPS score was determined to be 0.75 through the preliminary experiment. The registration error was measured after augmenting the virtual object by changing the weight ratio of the proposed method in the preliminary experiment. As a result of the preliminary experiment, it was confirmed that the CSA should not be completely excluded, but the DoI should be considered more. The performance of the proposed method was validated by comparing it with the conventional method in which markers were subjectively placed. It was confirmed that the proposed method performs better than the conventional method as follows. (1) The proposed method can provide more consistently accurate registration than the conventional method. (2) Regardless of the number of markers, the proposed method provides more accurate registration. This means that the proposed method can be applied in various ways, from environments using a small number of multiple markers to those using a large number of multiple markers, and it can become a baseline for placing multiple markers in research related to registration. The advantage of the proposed method is that it can replace the subjective human judgment when positioning multiple markers. Since human subjective judgment is highly volatile depending on the surrounding conditions or environments, it may have limitations in consistency and accuracy. However, the proposed method can ensure consistent performance and accuracy as it determines the positions of multiple markers by considering the CSA and the DoI of the object. The following studies are considered in future works. First, as the methods for extracting the interest points of virtual objects continue to evolve, studies are required to compare the performance of the proposed method using various interest point extraction methods. Second, a study is needed to verify the effect of the two thresholds used in the proposed method on registration performance based on the MPS Score. The proposed method used threshold \(\varepsilon\) for upscaling in the preprocessing step, and threshold \(2\varepsilon\) for calculating the DoI in the scoring step. Since these two thresholds are involved in the calculation of the MPS score, the effect of the threshold values should be closely examined in future research. Third, further research is needed to perform multifaceted sensitivity analyses by applying the proposed method to multiple large objects. Since the proposed method was carried out on two specific models with similar sizes, the set weight may be overfitting for vehicles. This implies that the parameters or formulas of the proposed method can be improved depending on the type or size. To compensate for this, it is necessary to apply the proposed method to multiple large objects of various types, not limited to vehicles, and to perform sensitivity analyses. Fourth, further research should be conducted to compare registration based on the proposed method with registration based on markerless methods. The registration performance of the proposed method was confirmed by comparing it with only the subjectively conventional method.