Monocular Model-based 3D Tracking of Rigid Objects
Many applications require tracking complex 3D objects. These include visual serving of robotic arms on specific target objects, Augmented Reality systems that require real time registration of the object to be augmented, and head tracking systems that sophisticated interfaces can use. Computer Vision offers solutions that are cheap, practical and non-invasive. Monocular Model-Based 3D Tracking of Rigid Objects reviews the different techniques and approaches that have been developed by industry and research. First, important mathematical tools are introduced: Camera representation, robust estimation and uncertainty estimation. Then a comprehensive study of the numerous approaches developed by the Augmented Reality and Robotics communities is given. The authors begin with those that are based on 1D or planar fiducial marks and move on to those that avoid the need to engineer the environment by relying on natural features such as edges, texture or interest points are detailed. Extensions to more specific applications that require the use of a motion model or multiple objects tracking are also discussed. The survey concludes with the different possible choices that should be made when implementing a 3D tracking system and a discussion of the future of vision-based 3D tracking. Because it encompasses many computer vision techniques from low-level vision to 3D geometry and includes a comprehensive study of the massive literature on the subject, Monocular Model-Based 3D Tracking of Rigid Objects is an invaluable reference for the student and researcher.
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3D model 3D points 3D pose 3D tracking affine transformation algorithm Analysis and Machine applications approach approximation ARToolKit Augmented Reality camera calibration matrix camera pose Computer Vision Conference on Computer constraints contours control points correspondences deformable descriptor detection discussed Equation Extended Kalman Filter extracted fast feature points fiducials Gauss-Newton Gauss-Newton algorithm gimbal lock gradient homography IEEE Transactions image features image gradients implementation interest points internal parameters invariant iteration keyframes keypoints least-squares linear locations M-estimators Machine Intelligence measurements methods minimization Mixed and Augmented model edge Model-Based motion model occlusions optical flow optimization orientation Pattern Analysis Pattern Recognition perspective projection pixels planar plane pose estimation predicted previous frame problem quaternion RANSAC real-time recovered recursive reliable rely require robot robust estimator rotation matrix scene segments skew-symmetric matrix solution Subsection Symposium on Mixed target object techniques textured tion tracker Transactions on Pattern vector Vision and Pattern vision-based wide baseline matching