Comments on: Cameras vs. Sensors

By: Adam

Adam — Wed, 05 Aug 2009 00:05:42 +0000

I don’t think it’s fair to say the GPS-based techniques will win since the applications are quite different. GPS-based techniques appear to be easier to implement so I agree that we will see more of these apps.

In general, GPS-based AR is good for navigation, tours, and other large-scale applications, while vision-based AR is better for object recognition at smaller scales. General object recognition is still quite hard though, so it’s natural that there will be fewer of these apps out there. This doesn’t mean these apps wouldn’t be more useful if they were available.

By: Thomas K Carpenter

Thomas K Carpenter — Mon, 03 Aug 2009 17:36:41 +0000

Hybrid of the two depending on the usage, mainly depending on the precision needed of the project. If you’re just doing location based information layers, then GPS is fine. If you’re getting down to the objects within those locations (like items in a grocery store), you’re going to need object recognition. As the technology improves, the usage will change too.

By: Alex Kasper

Alex Kasper — Mon, 03 Aug 2009 11:41:43 +0000

Aribtrary object recognition is far from being solved. Special cases in restricted environments have been solved, but I haven’t seen anything that’s close to being usable in an everyday environment.

By: Yulia Panina

Yulia Panina — Mon, 03 Aug 2009 08:42:23 +0000

We are using exactly this approach in our Google ADC2 entry: lightweight pattern recognition combined with Android’s pitch and roll sensor, far less computation is then needed to calculate extrinsic camera parameters.

By: Joe

Joe — Sun, 02 Aug 2009 21:22:21 +0000

The problem of recognizing an arbitrary object in any orientation without restricting (reasonable) lighting conditions has been solved? I know there are plenty of examples of vision systems recognizing the set of specific objects they’ve been trained on, and some of those more restrictive systems are even on mobiles (like SnapTouch Explorer). I just haven’t seen an example of a general solution.

By: serge

serge — Sun, 02 Aug 2009 21:16:17 +0000

“When vision researchers eventually solve the object recognition problem …”

Those problem mostly solved long ago. The problem how to squeeze those solutions into mobile device

By: Joe

Joe — Sun, 02 Aug 2009 21:10:45 +0000

Hasn’t dGPS been more or less superseded by WAAS, at least in the US? From what I understand they use the same sort of approach, only with WAAS transmitting its correction signals through a couple satellites. Carrier-phase GPS certainly has a lot of potential.

local RF beacon triangulation

Long-term, I think this is where it’s at. Like GPS they would work at night. Unlike GPS they could be sprinkled around indoors and anywhere else that it’s tough to get a GPS signal.

By: Noah Zerkin

Noah Zerkin — Sun, 02 Aug 2009 19:56:17 +0000

Hybrid. Taking the cue from our own perceptive abilities, I’d say that it makes sense to use as much data as one has at one’s disposal, within’ the limitations of one’s processing capabilities. Also, GPS is capable of more precise location fixing once you throw dGPS and eventually carrier-phase GPS into the mix. Feiner’s prototype system in the mid-90s featured dGPS. Perhaps with adoption of wearable AR systems we’ll see dGPS beacons domestically deployed more widely by the USCG, or deployed by somebody else with a bit more interest in the land-locked portions of the country. An ideal system might give accuracy weightings to all of the various elements of the equation based on environmental context. In urban areas, it might be possible to generate image-based “markers” from Google Street-View and Earth, and MS Photosynth imagery to generate a more precise fix than that possible with current consumer-accessible GPS. So the GPS and compass heading dramatically reduce the database set against which you need to compare your vision input. i.e. use GPS and magnetometer readings to set the context, and vision and/or local RF beacon triangulation for precision positioning where possible. In other words, I don’t really think it’s a “versus” situation at all, but one in which we’ll find more and more ways of using diverse and complementary data-sets to refine the gestalt. Sensors will only get cheaper and more accurate, embedded processors and GPUs faster, camera resolutions higher, served resources bigger, and mobile bandwidth broader. The key is in the knitting-together. It’s all about the convergence, methinks.

By: rouli

rouli — Sun, 02 Aug 2009 19:35:37 +0000

It seems that GPS&Compass based AR is more mature, and imho, it augments reality much more than any marker-bound technique.
On the other hand, there are some attractive vision based AR-like applications, such as GetFugu or Nokia’s point and find, which limits themselves to identification of 2d images.
I wonder how come no one created an application that merges the above two techniques. This could be a killer tourist application – walk the street of an European city using the GPS AR, enter a museum and look at images via the computer vision AR. Both are not really what the academy would call AR, but it’s a step in the right direction.