Construction of confidence regions for motion trajectories of objects in computer vision problems. (English. Russian original) Zbl 1278.93254
J. Comput. Syst. Sci. Int. 52, No. 3, 449-457 (2013); translation from Izv. Ross. Akad. Nauk, Teor. Sist. Upr. 2013, No. 3, 124-132 (2013).
Summary: The problem of finding an object lost for several number of frames is considered within the framework of motion analysis problem. A linear model of objects motion is designed on a finite time interval. The hypotheses on independence and normality of observation errors are tested. The Gauss-Markov estimate is found for motion parameters. Based on available measurements, hyperbolic confidence tubes are constructed for each of the coordinates of the center of mass of the moving object. The technique for derivation of the equation of an ellipse of dispersion for the two-dimensional Gauss vector of general form is demonstrated. The form of the ellipse of dispersion for the addressed problem is found. The results of testing the algorithm for open bases of video sequences PETS and ETISEO are presented.
MSC:
| 93E10 | Estimation and detection in stochastic control theory |
| 93E03 | Stochastic systems in control theory (general) |
| 94A08 | Image processing (compression, reconstruction, etc.) in information and communication theory |
| 93C83 | Control/observation systems involving computers (process control, etc.) |
Keywords:
Gauss-Markov estimate; observation errors; two-dimensional Gauss vector; objects motion; motion parameters; motion trajectories; motion analysis problem; hyperbolic confidence tubesReferences:
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