Abstract
The paper presents an improved method for estimating the number of moving people in a scene for video surveillance applications; the performance is measured on the public database used in the framework of the PETS international competition, and compared, on the same database, with the ones participating to the same contest up to now. The system exhibits a high accuracy, ranking it at the top positions, and revealed to be so fast to make possible its use in real time surveillance applications. © 2011 Springer-Verlag.
Cite
CITATION STYLE
Percannella, G., & Vento, M. (2011). A self-trainable system for moving people counting by scene partitioning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6754 LNCS, pp. 297–306). https://doi.org/10.1007/978-3-642-21596-4_30
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