ForGetMeNot

ForgetMeNot is a Desktop screensaver implemented in C/C++ for Ubuntu Linux. This application randomly chooses pictures from a selected folder and displays them with various degrees of blurring on the user’s screen during idle time. The images are replaced after a couple of seconds. The aim of the application is to provide the observer with memory cues to encourage them to proactively remember an event. Cues are given by the degree of de-blurring of the image and the degree of blurring is inversely related to time passed.

The main concept behind ForgetMeNot is that the degree of distortion is modeled as a function of time in the same fashion as Ebbinghaus' model for human memory retention. This model describes how the content of human memory fades away over time.

In ForgetMeNot, the model also determines the degree of distortion of the images, the rationale being that when images are fresh in memory fewer cues are needed. Hence, a freshly shot picture will be shown in a very blurry fashion. The more time passes by the clearer the images get. Hence, as images in our mind fade away and become cloudy, ForgetMeNot will reveal more and more details as retrieval cues in the randomly displayed images (noticeable over weeks). The application will therefore help compensate for loss of memory by off-loading to the clearer photos. It also provides an element of serendipity and surprise in its random selection.

Newer pictures, however, are not ‘served on a silver platter’, leaving it to the user to fill in strongly blurred (and thus missing) information by their imagination. Thus, ForgetMeNot was primarily designed for stimulating the observer’s memory. Due to the strong distortion of new pictures there is enough space for the mind to make up the story behind the photo. The application requires the observer to “participate in making meaning”, because of its ambiguous display.
This strategy is also supported by a study incorporating images taken by the Microsoft SenseCam device. Here test participants reported that the distortion of the SenseCam images eventually turned out to be a benefit; because they were incomplete, participants had to do more work to fill in the details and this promoted reflection on the pictures.

EyeOfDetail

As ForgetMeNot, EyeOfDetail also draws on notions of blurriness or fuzziness. This Desktop application is the attempt to create software that in a way maps and supports the concept of mindfulness. In philosophy and psychology, mindfulness is most commonly defined as a state of being attentive and aware of the present moment and of what is taking place around us. Higher levels of this distinct form of awareness and attention can have strong positive effects on wellbeing  and are associated with less emotional and cognitive disturbance.

The overall intention then of EyeOfDetail is to slow the observer down for a while, to focus attention and to encourage them to spend time, and deal in-depth, with the moment that is captured in the image. The application loads an image from data memory, blurs the pixels by Gaussian filtering and displays the modified content on a common LCD screen. While at first sight there is a loss of image quality and data, we hypothesise that the observer will actually be able to get more out of the image. To accomplish this, one small spot of the image is left un-blurred. This clearly visible spotting window is designed to focus the observer’s attention to one area at a time.
The setup of EyeOfDetail allows the user to coarsely navigate the position of the spot by wobbling an accelerometer device. Thus, the observer is capable of controlling what part of the image can be clearly examined. In doing so details can be discovered that would have been dwarfed by more prominent content of the original image. We choose to give the user control of the spot by an accelerometer in order to provide a different experience from the common screen-mouse interaction.

Demo (EyeOfDetail screen capturing):

Related Links and Images

• Güldenpfennig, F., & Fitzpatrick, G. (2011). Getting more out of your images: augmenting photos for recollection and reminiscence. Short Paper presented at the Proceedings of the 25th BCS Conference on Human-Computer Interaction, Newcastle-upon-Tyne, United Kingdom (pp.467-472). ACM. PDF.