Counting Moving People in Videos by Salient Points Detection

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 experiment...

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Bibliographic Details
Main Authors: Conte, D, Foggia, P, Percannella, G, Tufano, F, Vento, M
Format: Conference Proceeding
Language:English
Subjects:
Cameras
Clustering algorithms
Estimation
Pattern recognition
People counting
person detection
Robustness
Training
Video-surveillance
Videos
Online Access:Request full text
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Summary: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.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2010.431