@inproceedings{8cd6c29c69fe45f888865d419b428221,
title = "A multi-stage competitive neural networks approach for motion trajectory pattern learning",
abstract = "This paper puts forward a multi-stages competitive neural networks approach for motion trajectory pattern analysis and learning. In this method, the rival penalized competitive learning method, which could well overcome the competitive networks' problems of the selection of output neurons number and weight initialization, is used to discover the distribution of the flow vectors according to the trajectories' time orders. The experiments on different sites with CCD and infrared cameras demonstrate that our method is valid for motion trajectory pattern learning and can be used for anomaly detection in outdoor scenes.",
author = "Hejin Yuan and Yanning Zhang and Tao Zhou and Deng, {Fan G.An} and Xiuxiu Li and Huiling Lu",
year = "2007",
doi = "10.1007/978-3-540-72383-7_93",
language = "英语",
isbn = "9783540723820",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 1",
pages = "796--803",
booktitle = "Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings",
edition = "PART 1",
note = "4th International Symposium on Neural Networks, ISNN 2007 ; Conference date: 03-06-2007 Through 07-06-2007",
}