Structure estimation of a moving object using a moving camera: An unknown input observer approach

A state observer is designed for estimating the structure of a moving object with time-varying velocities seen by a moving camera. A nonlinear unknown input observer strategy is used where the object's velocity is considered as an unknown input to the perspective dynamical system. The object is assumed to be moving on a ground plane. The downward-looking camera observing the moving object is also moving (e.g., attached to an air vehicle) with known velocities. The developed method provides the first causal, observer-based structure estimation algorithm for a moving camera viewing a moving object with unknown time-varying object velocities.

[1]  Ashwin P. Dani,et al.  Structure and motion estimation of a moving object using a moving camera , 2010, Proceedings of the 2010 American Control Conference.

[2]  R. Rajamani Observers for Lipschitz nonlinear systems , 1998, IEEE Trans. Autom. Control..

[3]  Gérard G. Medioni,et al.  3D Reconstruction of Background and Objects Moving on Ground Plane Viewed from a Moving Camera , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[4]  Chia-Chi Tsui A new design approach to unknown input observers , 1996, IEEE Trans. Autom. Control..

[5]  S. Shankar Sastry,et al.  Two-View Multibody Structure from Motion , 2005, International Journal of Computer Vision.

[6]  E. Yaz,et al.  Observer design for discrete and continuous non-linear stochastic systems , 1993 .

[7]  Warren E. Dixon,et al.  Globally exponentially convergent observer for vision-based range estimation , 2010, 2010 IEEE International Symposium on Intelligent Control.

[8]  Pietro Perona,et al.  Reducing "Structure From Motion": A General Framework for Dynamic Vision Part 1: Modeling , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  M. Saif,et al.  A novel approach to the design of unknown input observers , 1991 .

[10]  H. Marquez,et al.  Design of unknown input observers for Lipschitz nonlinear systems , 2005, Proceedings of the 2005, American Control Conference, 2005..

[11]  Mina Teicher,et al.  A General Framework for Trajectory Triangulation , 2004, Journal of Mathematical Imaging and Vision.

[12]  John Oliensis,et al.  A Critique of Structure-from-Motion Algorithms , 2000, Comput. Vis. Image Underst..

[13]  D. Koenig,et al.  Design of a class of reduced order unknown inputs nonlinear observer for fault diagnosis , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[14]  Jaime A. Moreno,et al.  Unknown input observers for SISO nonlinear systems , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[15]  M. Saif,et al.  Unknown input observer design for a class of nonlinear systems: an LMI approach , 2006, American Control Conference.

[16]  D. Dawson,et al.  Range identification for perspective vision systems , 2003, Proceedings of the 2003 American Control Conference, 2003..

[17]  S. Bhattacharyya Observer design for linear systems with unknown inputs , 1978 .

[18]  Warren E. Dixon,et al.  Single Camera Structure and Motion , 2012, IEEE Transactions on Automatic Control.

[19]  O. Dahl,et al.  Nonlinear and Adaptive Observers for Perspective Dynamic Systems , 2007, 2007 American Control Conference.

[20]  M. Saif,et al.  Fault detection and isolation based on novel unknown input observer design , 2006, 2006 American Control Conference.

[21]  Richard I. Hartley,et al.  Multiple-View Geometry Under the {$L_\infty$}-Norm , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  M. Darouach,et al.  Full-order observers for linear systems with unknown inputs , 1994, IEEE Trans. Autom. Control..

[23]  Amnon Shashua,et al.  Trajectory Triangulation: 3D Reconstruction of Moving Points from a Monocular Image Sequence , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  B. Ghosh,et al.  Visually guided ranging from observations of points, lines and curves via an identifier based nonlinear observer , 1995 .

[25]  Mei Han,et al.  Reconstruction of a Scene with Multiple Linearly Moving Objects , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[26]  Yaser Sheikh,et al.  3D Reconstruction of a Moving Point from a Series of 2D Projections , 2010, ECCV.

[27]  Pramod P. Khargonekar,et al.  Lyapunov-based adaptive state estimation for a class of nonlinear stochastic systems , 2012, Autom..

[28]  Warren E. Dixon,et al.  Single Camera Structure and Motion Estimation , 2010 .

[29]  S. Shankar Sastry,et al.  An Invitation to 3-D Vision , 2004 .

[30]  M. Hou,et al.  Design of observers for linear systems with unknown inputs , 1992 .

[31]  Alan J. Laub,et al.  The LMI control toolbox , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[32]  Peter F. Sturm,et al.  A Factorization Based Algorithm for Multi-Image Projective Structure and Motion , 1996, ECCV.