Preliminary validation of Amped <scp>FIVE</scp> software for subject height estimation
Bibliographic record
Abstract
Single view metrology poses a persistent challenge in extracting accurate quantitative information from individual images or video frames within the realm of forensic video analysis. Methods such as reverse projection, projective geometry, and photogrammetry have been used in the past with success but require validation and understanding of the limitations of each method. This study aims to conduct a preliminary validation of the subject height estimation feature in Amped FIVE software, which relies on the principles of single view metrology. A group of 14 individuals assumed an upright posture at distances of 2.4 m, 5.4 m, and 10 m away from two security cameras with different resolutions 4k (3840 × 2160) and HD (1920 × 1080). Prior to recording, participants' heights were measured but were not provided to the researcher in this study until after the analysis was completed. A height scale with clearly marked black and white graduations was used as a control. Height estimations were subsequently obtained using the Measure 3D tool in Amped FIVE software. On average, the overall error was found to be approximately ± 1.3 cm with a standard deviation of 0.9 cm. This study shows that Amped FIVE can provide accurate height estimates in a controlled environment. Future work should be done to test more difficult scenarios in less-than-ideal conditions.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".