Reading #3: “Those Look Similar!” Issues in Automating Gesture Design Advice (Long)

COMMENTS:

Francisco Vides

SUMMARY:

This paper gives an overview of the Quill, a gesture design tool that allows developers to build applications using gesture recognition. The authors, Long, Landay and Rowe explore ways of improving Quill by providing feedback to users in order to help make their gestures better. In this case they experiment with giving advice to users when analysis of gestures determines that two gestures are too similar to be distinguished by people or the computer.

The authors begin by describing the study conducted to determine the criteria used to judge gesture similarity. Participants were asked to judge the similarity of gestures in three experiments: one and two involved selecting the most dissimilar gesture from many groups of three gestures, the third involved judging the similarity of pairs of gestures.

The overview of the experiments is followed by a description of quill and the gesture design process. Similarity metrics are used to analyze the gestures created to determine whether or not gestures are similar and possibly confusing. Advice for the user is then delivered in the form of unsolicited warnings.

Advice timing and content, as well as issues related to background analysis are some of the challenges encountered when the advice feature was implemented. The authors ultimately decided to allow actions to continue during gesture analysis and cancel analysis when an affecting change occurs.

DISCUSSION:

Providing feedback to help users make their designs less similar seems like a very useful feature to add to the quill application. These types of user aids are prevalent in many development environments today. However, I can see how the authors would have difficulty determining when and how to display helpful alerts, especially when they’re unsolicited. I would imagine that these types of alerts would be more annoying than helpful in cases where the information is wrong or unwanted. I think allowing some user control over feedback and when it’s delivered could also benefit this feature. This may have been alluded to in the future work and conclusions, but it was not completely clear to me.