High-speed pose and velocity measurement from vision

This paper presents a novel method for high speed pose and velocity computation from visual sensor. The main problem in high speed vision is the bottleneck phenomenon which limits the video rate transmission. The proposed approach circles the problem out by increasing the information density instead of the data rate transmission. This strategy is based on a rotary sequential acquisition of selected regions of interest (ROI) which provides space-time data. This acquisition mode induces an image projection deformation of dynamic objects. This paper shows how to use this artifact for the simultaneous measure of both pose and velocity, at the same frequency as the ROI's acquisition one.

[1]  Philippe Martinet,et al.  Simultaneous Object Pose and Velocity Computation Using a Single View from a Rolling Shutter Camera , 2006, ECCV.

[2]  Houyuan Jiang,et al.  Global and Local Superlinear Convergence Analysis of Newton-Type Methods for Semismooth Equations with Smooth Least Squares , 1998 .

[3]  Peter I. Corke,et al.  A tutorial on visual servo control , 1996, IEEE Trans. Robotics Autom..

[4]  Michel Dhome,et al.  Do We Really Need an Accurate Calibration Pattern to Achieve a Reliable Camera Calibration? , 1998, ECCV.

[5]  Jacques Gangloff,et al.  High-speed visual servoing of a 6-d.o.f. manipulator using multivariable predictive control , 2003, Adv. Robotics.

[6]  Joel Falcou,et al.  An object oriented SIMD library. , 2005 .

[7]  Nicolas Andreff,et al.  Simplifying the kinematic calibration of parallel mechanisms using vision-based metrology , 2006, IEEE Transactions on Robotics.

[8]  Larry S. Davis,et al.  Model-based object pose in 25 lines of code , 1992, International Journal of Computer Vision.

[9]  Joel Falcou,et al.  E.V.E., An Object Oriented SIMD Library , 2005, Scalable Comput. Pract. Exp..

[10]  Ulrich Muehlmann,et al.  A new high speed cmos camera for real-time tracking applications , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[11]  Radu Horaud,et al.  Object pose from 2-D to 3-D point and line correspondences , 1995, International Journal of Computer Vision.

[12]  Masatoshi Ishikawa,et al.  1 ms column parallel vision system and its application of high speed target tracking , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[13]  Anastasis A. Sofokleous,et al.  Review: H.264 and MPEG-4 Video Compression: Video Coding for Next-generation Multimedia , 2005, Comput. J..

[14]  Iain E. G. Richardson,et al.  H.264 and MPEG-4 Video Compression: Video Coding for Next-Generation Multimedia , 2003 .

[15]  Vincenzo Lippiello,et al.  Adaptive extended Kalman filtering for visual motion estimation of 3D objects , 2007 .

[16]  S. Shankar Sastry,et al.  Geometric Models of Rolling-Shutter Cameras , 2005, ArXiv.

[17]  Patrick Rives,et al.  A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..

[18]  William J. Wilson,et al.  Relative end-effector control using Cartesian position based visual servoing , 1996, IEEE Trans. Robotics Autom..