A Multiple DSP-based 3D Laser Range Sensor and its Application to Real-Time Motion Detection
Bibliographic record
Abstract
This report describes the implementation of an auto-synchronised 3D laser range scanner and its application to motion detection. The 3D motion detector (3DMD) uses a 3D laser scanner to detect the motion of an object and to display that motion in real-time. The system is based on a real-time modular digital signal processor (DSP) architecture called MDSP. 3DMD is a PC-based system that contains an array of embedded DSP processors that communicate using dedicated communication links. The scalable DSP system is based on a message communication model, rather than a shared memory model. The software is based on Precise/MQX, a commercial real-time operating system. The report describes the principle of operation of 3DMD and describes in detail the hardware and software configuration. The report includes some practical information about how to load and run the system demonstration, and how to develop application software for 3DMD. It concludes with some preliminary performance results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".