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Record W2051154604 · doi:10.1117/12.460176

<title>MDSP: a modular DSP architecture for a real-time 3D laser range sensor</title>

2002· article· en· W2051154604 on OpenAlexaff
David A. Green, François Blais, J.‐A. Beraldin, Luc Cournoyer

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsComputer scienceModular designComputer visionComputer graphics (images)Artificial intelligenceDigital cameraFlash (photography)Frame rateImage sensorComputer hardwareOptics

Abstract

fetched live from OpenAlex

As electronic documents are becoming more and more popular, variety of objects, including 2D and 3D objects such as articles, books and 3D-shapes, can be easily contained in a document. Conventional systems cannot capture these objects as a 3D form. We developed a new image capturing system with 3D information for deskwork. It is an assemblage of a normal digital camera and its docking station designed for easy operation. The docking station swings the attached camera tilting step by step. Within a few steps, it covers the whole object automatically. Then each frame is combined together into one complete image with full resolution. In order to get precise 3D structure, stripe patterns are projected by a modified flash light attached on the camera. The resolution rises by means of the swing to be slipped the patterns on the object. Using the obtained 3D data we can reconstruct a correct image from a splay surface image such as a book. Experimental Results of image mosaicing and 3D reconstruction shows that the system is practical.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.225
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations8
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Vision and ImagingFrench-language works237,207