scholarly journals Finding focus in a difficult landscape: Therapists’ experiences with challenging video guidance processes for parent–infant dyads

2020 ◽  
Vol 41 (6) ◽  
pp. 743-756
Author(s):  
Indra Simhan ◽  
Marius Veseth ◽  
Kari Vik ◽  
Aslak Hjeltnes
Keyword(s):  
Video Guidance

Video guidance sensor flight experiment results

1998 ◽  
Author(s):  
Richard T. Howard ◽  
Thomas C. Bryan ◽  
Michael L. Book
Keyword(s):  
Flight Experiment ◽  
Video Guidance

scholarly journals Advanced Video Guidance Sensor (AVGS) development testing

2004 ◽  
Author(s):  
Richard T. Howard ◽  
Albert S. Johnston ◽  
Thomas C. Bryan ◽  
Michael L. Book
Keyword(s):  
Video Guidance

scholarly journals Performance Characterization of the Smartphone Video Guidance Sensor as Vision-Based Positioning System

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5299
Author(s):  
Nasir Hariri ◽  
Hector Gutierrez ◽  
John Rakoczy ◽  
Richard Howard ◽  
Ivan Bertaska
Keyword(s):  
Sampling Rate ◽  
Target Velocity ◽  
Error Statistics ◽  
Operational Conditions ◽  
Error Metrics ◽  
Orientation Vector ◽  
State Position ◽  
Overall Performance ◽  
Video Guidance

The Smartphone Video Guidance Sensor (SVGS) is a vision-based sensor that computes the six-state position and orientation vector of a target relative to a coordinate system attached to a smartphone. This paper presents accuracy-characterization measurements of the Smartphone Video Guidance Sensor (SVGS) to assess its performance as a position and attitude estimator, evaluating its accuracy in linear and angular motion for different velocities and various types of targets based on the mean and standard deviation errors between SVGS estimates and known motion profiles, in both linear and angular motions. The study also examines the effects of target velocity and sampling rate on the overall performance of SVGS and provides an overall assessment of SVGS’ performance as a position/attitude estimator. While the error metrics are dependent on range and camera resolution, the results of this paper can be scaled to other operational conditions by scaling the blob size in pixels (the light markers identified in the images) relative to the total resolution (number of pixels) of the image. The error statistics of SVGS enable its incorporation (by synthesis of a Kalman estimator) in advanced motion-control systems for navigation and guidance.

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