Abstract
We estimate the speed of texture change by measuring the spread of texture vectors in their feature space. This method allows us to robustly detect even very slow moving objects. By learning a normal amount of texture change over time, we are also able to detect increased activities in videos. We illustrate the performance of the proposed techniques on videos from PETS repository and the Temple University Police department. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Latecki, L. J., Miezianko, R., & Pokrajac, D. (2005). Activity and motion detection based on measuring texture change. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3587 LNAI, pp. 476–486). Springer Verlag. https://doi.org/10.1007/11510888_47
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
