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structured light-based sensor primesense carmine 1.09  (PrimeSense Ltd)

 
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    PrimeSense Ltd structured light-based sensor primesense carmine 1.09
    Structured Light Based Sensor Primesense Carmine 1.09, supplied by PrimeSense Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/structured light-based sensor primesense carmine 1.09/product/PrimeSense Ltd
    Average 90 stars, based on 1 article reviews
    structured light-based sensor primesense carmine 1.09 - by Bioz Stars, 2026-06
    90/100 stars

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    Image Search Results


    Structured light sensor analyzed: ( a ) Einscan-Sp by Shining 3D, ( b ) Leo by Artec 3D.

    Journal: Materials

    Article Title: Optical Characterization of Materials for Precision Reference Spheres for Use with Structured Light Sensors

    doi: 10.3390/ma16155443

    Figure Lengend Snippet: Structured light sensor analyzed: ( a ) Einscan-Sp by Shining 3D, ( b ) Leo by Artec 3D.

    Article Snippet: The other structured light sensor analyzed is a Leo (Artec 3D, Luxembourg) [ ], shown in b, whose main features are presented in .

    Techniques:

    Non-contact sensors’ technology classification: SL = Structured-Light, ToF = Time-of-Flight, LiDAR = Light Detection and Ranging, CCD = charge coupled device.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

    doi: 10.3390/s20247252

    Figure Lengend Snippet: Non-contact sensors’ technology classification: SL = Structured-Light, ToF = Time-of-Flight, LiDAR = Light Detection and Ranging, CCD = charge coupled device.

    Article Snippet: 2014 , Tahavori et al. [ ] , Respiratory motion , D: multi-ROI analysis, to investigate the dominate variations using PCA, based on depth data from a structured light sensor. V: multi-ROI analysis performed on 3 separate sessions. S: 20 subjects. , The first principal component describes more than 70% of the motion data variance in thoracic and abdominal surfaces. , Clinical environment ▪ Abnormality detection. ▪ Analysis of disease severity..

    Techniques:

    Comparison of depth sensors.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

    doi: 10.3390/s20247252

    Figure Lengend Snippet: Comparison of depth sensors.

    Article Snippet: 2014 , Tahavori et al. [ ] , Respiratory motion , D: multi-ROI analysis, to investigate the dominate variations using PCA, based on depth data from a structured light sensor. V: multi-ROI analysis performed on 3 separate sessions. S: 20 subjects. , The first principal component describes more than 70% of the motion data variance in thoracic and abdominal surfaces. , Clinical environment ▪ Abnormality detection. ▪ Analysis of disease severity..

    Techniques: Comparison

    Recent RGB-D sensors: structured-light (Kinect v1, Asus Xtion Pro, Intel SR300), time-of-flight (Kinect v2, Kinect Azure DK, VicoVR), and active stereo vision (Intel R200, D435).

    Journal: Sensors (Basel, Switzerland)

    Article Title: Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

    doi: 10.3390/s20247252

    Figure Lengend Snippet: Recent RGB-D sensors: structured-light (Kinect v1, Asus Xtion Pro, Intel SR300), time-of-flight (Kinect v2, Kinect Azure DK, VicoVR), and active stereo vision (Intel R200, D435).

    Article Snippet: 2014 , Tahavori et al. [ ] , Respiratory motion , D: multi-ROI analysis, to investigate the dominate variations using PCA, based on depth data from a structured light sensor. V: multi-ROI analysis performed on 3 separate sessions. S: 20 subjects. , The first principal component describes more than 70% of the motion data variance in thoracic and abdominal surfaces. , Clinical environment ▪ Abnormality detection. ▪ Analysis of disease severity..

    Techniques: