Summary:
This paper focuses on "the segmentation problem" -- discriminating between two or more fluidly connected gestures. The authors emphasize that their approach is recognition-led: rather than looking at what gestures would be useful for a particular interface and creating a recognizer for just those, they are making recognizers that could possibly be incorporated into various interfaces. They divide gestures into postures and gestures (static & dynamic), and each of these groups is divided by whether or not hand motion and orientation are considered (giving categories like Static Posture Static Location: SPSL -- similarly, DPSL, SPDL, DPDL, in order of complexity). Segmenting gestures from a less complex class is easier than from a more complex class. They suggest that fingertip acceleration maxing away from the body may indicate an intention to produce another gesture. They also suggest considering the minima on the hand tension graph or other changes in the graph's shape. They give an equation to model finger tension based on finger-joint angles. Tension is considered as a sum of the tension in each finger.
They tested the hand tension model with two sets of data using a Mattel Power Glove, which scores finger bentness from 1-4 on 4 fingers. They tried two BSL sentence fragments: "MY NAME" and "MY NAME ME". The graphs indicate tension maximizes where the intentional postures occur and minima occurs between them. They admit that more data is a necessary next step before firm conclusions can be made.
Discussion:
This paper seems to focus on the equivalent of recognizing sketched geometric primitives so as to eventually be able to recognize complex shapes made up of them, which makes it an excellent followup to recent class discussion. Supposing that they didn't choose an overly easy pair of sample sentence fragments to segment, their approach seems pretty promising, and even if most gestures don't turn out to divide well based on tension, it seems likely that it will be worth including in some way for the cases where it is useful. I wonder if it would be worth having some sensor of tension in the glove, supposing the glove fits well, maybe using a elastic string along the inside/outside of the finger that stretches and puts pressure on a sensor or falls slack and doesn't, and if this would compare favorably to the kind of angle-based tension that they are talking about or if it is just redundant and unnecessary.
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3 comments:
Yes, I think there could be many ways to measure or model the hand tension, maybe some better gloves or better tension models. But, anyway, this paper presents a good cue to do the segmentation, and I believe there will be some other similar work following this paper's approach.
physically modeling hand tension from the device would be nice, but i wonder if that would make the glove more obtrusive than what it already (arguably) is. it may be and it may not be - i don't really know. for glove like the p5 glove it probably wouldn't be that big of a deal since there is already that black rubbery piece behind each one of the fingers. maybe someone could take advantage of that part of the p5 glove to maybe add a way to calculate tension directly.
I think physically modeling hand tension in a glove would force a user's "glove resting position" to be slightly different than their normal relaxed position. The added pressure on a user's fingers would then force users to want to rest their hands, so their hypothesis would be self-fulfilling.
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