3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation

The causal estimation of three-dimensional motion from a sequence of two-dimensional images can be posed as a nonlinear filtering problem. We describe the implementation of an algorithm whose uniform observability, minimal realization and stability have been proven analytically in [5]. We discuss a scheme for handling occlusions, drift in the scale factor and tuning of the filter. We also present an extension to partially calibrated camera models and prove its observability. We report the performance of our implementation on a few long sequences of real images. More importantly, however, we have made our real-time implementation ? which runs on a personal computer ? available to the public for first-hand testing.

• Type: Conference
• Year: 2000
• Where: ECCV
• Authors: Alessandro Chiuso, Paolo Favaro, Hailin Jin, Stefano Soatto
• Keywords: Causal Estimation, Computer Vision, ECCV 2000, Minimal Realization, Nonlinear Filtering Problem, Real-time Implementation, Two-dimensional Images