Model-based object pose in 25 lines of code
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Locating Facial Region of a Head-and-Shoulders Color Image
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Real-Time Non-Rigid Surface Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
An Active System for Three-Dimensional Localization of Mobile Robots
Journal of Intelligent and Robotic Systems
Temporal Range Registration for Unmanned Ground and Aerial Vehicles
Journal of Intelligent and Robotic Systems
From motion capture data to character animation
Proceedings of the ACM symposium on Virtual reality software and technology
A survey of skin-color modeling and detection methods
Pattern Recognition
Modeling and massage control of human skin muscle by using multi-fingered robot hand
Integrated Computer-Aided Engineering - Informatics in Control, Automation and Robotics
Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation
International Journal of Computer Vision
Robust 3D Marker Localization Using Multi-spectrum Sequences
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
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Locating the 3D positions of the points on the human back is an essential issue in stereo-based interactive robotic back massage machines. In stereoscopic 3D localization, the 3D positions are determined from the corresponding image points captured by calibrated stereo cameras. However, detecting these corresponding points on the human back is highly challenging due to the smooth and texture-less characteristics of human skin. In the present study, this problem is resolved by means of a novel correspondences detection scheme designated as Correspondences from Epipolar geometry and Contours via Triangle barycentric coordinates (CECT). In the proposed approach, reliable correspondences are extracted from the edge contours of the human back by applying epipolar geometry, and these correspondences are then used to compute the correspondences of the featureless points within the edge contour using a triangle barycentric coordinate approach. The accuracy and robustness of the estimated correspondences are ensured by applying three geometric constraints, namely a similarity constraint, a shape constraint and an epipolar constraint. The performance of the proposed approach is demonstrated by means of a series of experiments involving 28 subjects and four different testing conditions. In addition, the accuracy of the proposed localization scheme is evaluated by comparing the estimated 3D positions with those obtained using the cun-based measurement method in Traditional Chinese Medicine (TCM).