Abstract
A fast algorithm for the detection of independently moving objects by an also moving observer by means of investigating optical flow fields is presented. Since the measurement of optical flow is a computationally expensive operation, it is necessary to restrict the number of flow measurements. The proposed algorithm uses two different ways to determine the positions, where optical flow is calculated. A part of the positions is determined using a particle filter, while the other part of the positions is determined using a random variable, which is distributed according to an initialization distribution. This approach results in a restricted number of optical flow calculations leading to a robust real time detection of independently moving objects on standard consumer PCs.
This work was supported by BMBF Grant No. 1959156C.
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Woelk, F., Koch, R. (2004). Fast Monocular Bayesian Detection of Independently Moving Objects by a Moving Observer. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds) Pattern Recognition. DAGM 2004. Lecture Notes in Computer Science, vol 3175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28649-3_4
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DOI: https://doi.org/10.1007/978-3-540-28649-3_4
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