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Structure from motion causally integrated over time

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4 Author(s)
A. Chiuso ; Dipt. di Elettronica e Inf., Padova Univ., Italy ; P. Favaro ; Hailin Jin ; S. Soatto

We describe an algorithm for reconstructing three-dimensional structure and motion causally, in real time from monocular sequences of images. We prove that the algorithm is minimal and stable, in the sense that the estimation error remains bounded with probability one throughout a sequence of arbitrary length. We discuss a scheme for handling occlusions (point features appearing and disappearing) and drift in the scale factor. These issues are crucial for the algorithm to operate in real time on real scenes. We describe in detail the implementation of the algorithm, which runs on a personal computer and has been made available to the community. We report the performance of our implementation on a few representative long sequences of real and synthetic images. The algorithm, which has been tested extensively over the course of the past few years, exhibits honest performance when the scene contains at least 20-40 points with high contrast, when the relative motion is "slow" compared to the sampling frequency of the frame grabber (30 Hz), and the lens aperture is "large enough" (typically more than 30° of visual field)

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:24 ,  Issue: 4 )