Visual Odometry Using 3-Dimensional Video Input
Why this work is in the frame
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Bibliographic record
Abstract
Using Visual Odometry a robot can track its trajectory using video input. This allows more accurate ego-motion estimation when compared to classical odometry which relies on measurement of wheel motion. The Microsoft Kinect sensor provides 3D imagery, similar to a LASER or LIDAR scanner, which can be used for visual odometry with a single sensor. This diers from usual implementations that require stereo vision with two or more standard image sensors. The system has advantages over a laser scanner in that it provides a video image as well as depth information such that matching using feature detectors such as SIFT or SURF is possible. Visual odometry is performed by matching 3D points that have 2D descriptors. This paper presents and implements a visual odometry system for a mobile robot that utilizes feature detection and tracking combined with a low cost 3D video sensor, Microsoft's Kinect.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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