## 10 Conclusion and Future Work  
We approached the study of object manipulation for markerless AR by examining the results from prior marker AR research and selecting potentially effective methods. MOD IVI was proposed to modify and enhance the IVI method, the latest and seemingly best marker AR method, to support the manipulation of large-scale objects. In addition to adopting the testing protocol and test cases from previous marker AR studies, new test cases were derived to assess the methods in light of the significantly reduced constraints on virtual object size, augmented space dimension, inter-object occlusion, and freedom of user movement. Our testing results showed that users found it difficult to manipulate objects based on a combination of physical one-to-one proxy movements and logical touch screen control. However, in all cases, users were efficient when the one-to-one proxy manipulation was consistently involved: IVI (or MOD IVI) for the small-scale cases and HOMER-S for the large-scale cases. This result is not surprising because markerless AR attempts to naturally augment virtual objects. It is instinctive for users to attempt to pick up an object and perform the exact movement and rotation needed by treating the handheld device as a proxy. When the scale of objects is small, users can efficiently pick up and perform object movement/rotation as one continuous action. However, when object sizes are large, users prefer separating the manipulation into distinct selection, movement, and rotation steps. This difference in preference seems intuitive. Consider in real life, the cases of moving a small object, e.g., a pencil, versus a large and potentially heavy object, e.g., a sofa. In the former, it is likely that the pencil manipulation is performed as a single continuous action, whereas for the sofa, it is conceivable that the sofa movement and rotation are purposely planned and carried out as distinct steps. The proposed MOD IVI method did not significantly outperform any existing methods. Recalling the lesson learnt from the hybrid test results, for the case of markerless AR, users found it awkward to combine physical device and logical touch screen manipulations. In alignment with this observation, the proposed touch screen modifications to the IVI methods were not welcomed by users. However, Test 3 results do indicate that changing the transparency of selected objects is an effective addition. Although our testers were gender balanced, they were uniformly technologically inclined, eager, and excited by recent AR advancements. We believe that this uniformity resulted in heavily biased opinion poll results. Additionally, our augmented space was in a research lab, and the virtual objects were uniformly simple geometric shapes. It is difficult to generalize how users may strategize and carry out object manipulations in other settings. The direct object manipulation methods studied and the associated conclusions are targeted at markerless AR applications. Currently, markerless AR capability is enabled via depth-sensing capability. It is important to note that our study is independent from the underlying depth-sensing implementation technology. The key issues are devices that are capable in sensing, approximating, and \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Average** & **Practice Time** & **Comfort Level** & **Ease of Use** & **Speed** & **Accuracy** \\ \hline
**Average (max of 7)** & 6.15 & 6.49 & 6.12 & 6.37 & 6.47 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: User feedback from posttest questionnaire. augmenting the physical environment without explicit placements of markers as well as devices with the ability to support the selection and manipulation of virtual objects in the augmented environment. The mobile consumer market continues to undergo rapid changes. Since our study, support for mobile AR devices seems to be moving away from the more accurate but resource-demanding depth-sensing hardware.