Counting crowd flow based on feature points
Neurocomputing
| Hi-index | 0.00 |
This paper presents a novel method to count people for video surveillance applications. The problem is faced by establishing a mapping between some scene features and the number of people. Moreover, the proposed technique takes specifically into account problems due to perspective. In the experimental evaluation, the method has been compared with respect to the algorithm by Albiol et al., which provided the highest performance at the PETS 2009 contest on people counting, using the same datasets. The results confirm that the proposed method improves the accuracy, while retaining the robustness of Albiol's algorithm.