Dynamic structure from motion based on nonlinear adaptive observers

Structure and motion estimation from long image sequences is a an important and difficult problem in computer vision. We propose a novel approach based on nonlinear and adaptive observers based on a dynamic model of the motion. The estimation of the threedimensional position and velocity of the camera as well as the three-dimensional structure of the scene is done by observing states and parameters of a nonlinear dynamic system, containing a perspective transformation in the output equation, often referred to as a perspective dynamic system. An advantage of the proposed method is that it is filter-based, i.e. it provides an estimate of structure and motion at each time instance, which is then updated based on a novel image in the sequence. The observer demonstrates a trade-off compared to a more computer vision oriented approach, where no specific assumptions regarding the motion dynamics are required, but instead additional feature points are needed. Finally, the performance of th...

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Ola Dahl, Anders Heyden
• Keywords: Computer Vision, Dynamic System, ICPR 2008, Motion Estimation, Nonlinear Dynamic System