A team from the University of Tokyo have conceived of several new applications for lasers, some of which are interesting to say the least, others potentially groundbreaking. These applications arise from their Smart Laser Scanner (markerless laser tracking) technology:
Essentially, it is a smart rangefinder scanner that instead of continuously scanning over the full field of view, restricts its scanning area to a very narrow window precisely the size of the target (from the Ishikawa Komura Laboratory)
So what this means for us is we could pretty soon have a low-cost and low-apparatus method to interface with a wearable computer, in multitouch, and without the need for any markers.
The project website features videos for all of their experiments, including:
Simple 3D tracking
Multiple point tracking
I urge you to read more on the project website right here, but before you go, I’d like to feature one of the coolest applications I found for the Smart Laser Scanner. It’s called Sticky Light, and it’s an experiment in light interaction:
The question I want to ask is, wouldn’t this be the ultimate executive toy if productized in time for Christmas? I know I want one.
Presently, most AR research is concerned with live video imagery and it’s processing, which allows the addition of live-rendered 3D digital images. This new augmented reality is viewable through a suitably equipped device, which incorporates a camera, a screen and a CPU capable of running specially developed software. This software is written by specialist software programmers, with knowledge of optics, 3D-image rendering, screen design and human interfaces. The work is time consuming and difficult, but since there is little competition in this field, the rare breakthroughs that do occur are as a result of capital investment: something not willingly given to developers of such a nascent technology.
What is exciting about AR research is that once the work is done, its potential is immediately seen, since in essence it is a very simple concept. All that is required from the user is their AR device and a real world target. The target is an object in the real world environment that the software is trained to identify. Typically, these are specially designed black and white cards known as markers:
These assist the recognition software in judging viewing altitude, distance and angle. Upon identification of a marker, the software will project or superimpose a virtual object or graphical overlay above the target, which becomes viewable on the screen of the AR device. As the device moves, the digital object orients in relation to the target in real-time:
The goal of some AR research is to free devices from markers, to teach AR devices to make judgements about spatial movements without fixed reference points. This is the cutting edge of AR research: markerless tracking. Most contemporary research, however, uses either marker-based or GPS information to process an environment.
Marker-based tracking is suited to local AR on a small scale, such as the Invisible Train Project (Wagner et al., 2005) in which players collaboratively keep virtual trains from colliding on a real world toy train track, making changes using their touch-screen handheld computers:
GPS tracking is best applied to large scale AR projects, such as ARQuake (Thomas et al, 2000), which exploits a scale virtual model of the University of Adelaide and a modified Quake engine to place on-campus players into a ‘first-person-shooter’. This application employs use of a headset, wearable computer, and a digital compass, which offer the effect that enemies appear to walk the corridors and ‘hide’ around corners. Players shoot with a motion-sensing arcade gun, but the overall effect is quite crude:
More data input would make the game run smoother and would provide a more immersive player experience. The best applications of AR will exploit multiple data inputs, so that large-scale applications might have the precision of marker-based applications whilst remaining location-aware.
Readers of this blog will be aware that AR’s flexibility as a platform lends applicability to a huge range of fields:
Current academic work uses AR to treat neurological conditions: AR-enabled projections have successfully cured cockroach phobia in some patients (Botella et al., 2005);
There are a wide range of civic and architectural uses: Roberts et al. (2002) have developed AR software that enables engineers to observe the locations of underground pipes and wires in situ, without the need schematics
AR offers a potentially rich resource to the tourism industry: the Virtuoso project (Wagner et al., 2005) is a handheld computer program that guides visitors around an AR enabled gallery, providing additional aural and visual information suited to each artefact;
The first commercial work in the AR space was far more playful, however: AR development in media presentations for television has led to such primetime projects as Time Commanders (Lion TV for BBC2, 2003-2005) in which contestants oversee an AR-enabled battlefield, and strategise to defeat the opposing army, and FightBox (Bomb Productions for BBC2, 2003) in which players build avatars to compete in an AR ‘beat-em-up’ that is filmed in front of a live audience; T-Immersion (2003- ) produce interactive visual installations for theme parks and trade expositions; other work is much more simple, in one case the BBC commissioned an AR remote-control virtual Dalek meant for mobile phones, due for free download from BBC Online:
The next entry in this series is a case study in AR development. If you haven’t already done so, please follow me on Twitter or grab an RSS feed to be alerted when my series continues.