Camera Calibration with Distortion Models and Accuracy Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
SIAM Journal on Optimization
A Four-step Camera Calibration Procedure with Implicit Image Correction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Kinect-based system for cognitive rehabilitation exercises monitoring
Computer Methods and Programs in Biomedicine
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This article presents a Matlab-based stereo-vision motion tracking system (SVMT) for the detection of human motor reactivity elicited by sensory stimulation. It is a low-cost, non-intrusive system supported by Graphical User Interface (GUI) software, and has been successfully tested and integrated in a broad array of physiological recording devices at the Human Physiology Laboratory in the University of Granada. The SVMT GUI software handles data in Matlab and ASCII formats. Internal functions perform lens distortion correction, camera geometry definition, feature matching, as well as data clustering and filtering to extract 3D motion paths of specific body areas. System validation showed geo-rectification errors below 0.5mm, while feature matching and motion paths extraction procedures were successfully validated with manual tracking and RMS errors were typically below 2% of the movement range. The application of the system in a psychophysiological experiment designed to elicit a startle motor response by the presentation of intense and unexpected acoustic stimuli, provided reliable data probing dynamical features of motor responses and habituation to repeated stimulus presentations. The stereo-geolocation and motion tracking performance of the SVMT system were successfully validated through comparisons with surface EMG measurements of eyeblink startle, which clearly demonstrate the ability of SVMT to track subtle body movement, such as those induced by the presentation of intense acoustic stimuli. Finally, SVMT provides an efficient solution for the assessment of motor reactivity not only in controlled laboratory settings, but also in more open, ecological environments.