Motion-path based gesture interaction with smart home services
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we propose a motion-path based gesture recognition technique and show its application in a smart home environment. Users hand gestures are recognized by capturing the motion-path while they draw different symbols in the air. In order to capture the motion-path, we use infra-red camera's IR sensing capability. The IR camera tracks the infra-red emitter attached to the user's hand gloves and produces a sequence of motion-points, which are then analyzed syntactically to recognize the intended hand gesture. The recognized gesture is used to interact with the intelligent environment for accessing various services. Toggling a lamp switch, changing the light intensity, and playing/pausing a movie are few examples where we have integrated the gesture-based interaction. Our experiment shows that the proposed gesture recognition technique is robust and its use in the smart home environment is interesting and appealing to the people.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it