# A Review on Methods and Systems for Remote Collaboration
## 5 Communication Methods and Cues
### Pointers and Annotations  
One of the first methods applied in remote assistance was a reality-augmenting telepointer controlled remotely to guide the local user [26]. The results of this approach showed that a remote user could effectively guide and direct a local user's activities. The participants of the study conducted in [99] for remote construction of a robot valued the pointing device because it helped them to make references to objects faster than they could with video. The visible light path laser projector (VLLP) described in [100] was equipped with a laser projector and a mist generator. This solution had the advantage that the laser projector, VLLP, could instruct with not only a laser spot but also with simple line drawings. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Visual Display Methods**} \\ \cline{2-6}
**Application** & \multirow{2}{*}{**2D View**} & \multirow{2}{*}{**3D View**} & \multirow{2}{*}{**VR**} & \multirow{2}{*}{**AR**} & \multirow{2}{*}{**MR**} & **360-Degree** \\
**(Task Type)** & & & & & **Panorama** \\ \hline Healthcare & [61] & & & & \\ \hline Object Reconstruction & [62] & & [62] & & \\ \hline Assembly Task & [63] & & & & \\ \hline Physical Task & [64] & & & [64] & \\ \hline Car Maintenance & [65] & & & [65] & \\ \hline Object Manipulation & [66; 79; 80; 87; 92] & [66; 79; 81; 83; 84; 85; 86; 87; 94] & [66; 83; 87; 94] & [66; 79; 80; 83; 87; 93; 87; 93; 64] & [66; 81; 82; 83; 84; 86; 87; 93; 94] \\ \hline Lego Assembly & & [72; 73] & [72; 73] & & [72; 73] & \\ \hline Maintenance & [74] & [74; 78] & [74; 78] & [74; 78] & & \\ \hline Maintenance—Industry & [77] & & & [77] & \\ \hline Object Identification & & [71] & [71] & [71; 90; 91] & [88; 89; 90; 91] \\ \hline Maintenance—Hydroelectric & & & [92] & & [92] \\ Power Plant & & & & & [92] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Visual display methods used in remote collaboration. A new setup was presented in [101], where a remote expert could annotate, point, and draw on the local worker's objects using a laser projector. At the time that it was developed, this method was intended to support pre- and post-surgical consultations between a surgeon and a remotely located patient. A prototype system that enables a mobile worker to receive guidance from a remote helper in real time using freehand sketches projected directly onto the worker's environment is presented in [31]. A study comparison of the use of pointers and annotations in live video and still images was performed in [102]. The results showed that users collaborate more efficiently using annotation cues than pointer cues for communicating object position and orientation information. [PERSON] [103] showed how Chili, a mobile phone call system, can provide on-video drawing capabilities and control of the viewpoint. [PERSON] proved, in his research on augmented visual communication cues [104], that both pointers and annotation could improve the feeling of being more connected, understanding the remote partner, and being together. StickyLight [105] is a system based on a pico projector that allows a worker to draw annotations in the real local user's environment. The expert can draw and point via his tablet, which is connected to the local user's PC. The pico projector is paired with the local user's computer and performs the actions that the remote user is drawing. [PERSON] et al., in their study about stabilized annotations [106], found that, by freezing the video, the temporal stabilization of the annotations was efficient if the camera did not have a fixed position. In this scenario, it could be difficult for the remote collaborator to return to live video if the viewed perspective was changed. Stabilized annotations proved to be useful when referencing objects but not when pointing or simulating object manipulation. The research found that, overall, users preferred stabilized annotations, even though they did not outperform non-stabilized annotations in all tasks.