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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: