Paper Info
Title
Analysis of Multi-planar Probability Maps for People Localization in Overlapping Camera Systems
Abstract
This paper proposes a novel method for people localization in multi-camera video surveillance systems. Multi-planar projections of overlapping views are fused to obtain probability maps known as synergy maps. However, synergy maps suffer from false detections known as ghosts, and the purpose of this article is to use pattern recognition techniques for ghost pruning. To this end, the geometry of the system is used to generate synthesized synergy maps corresponding to the presence of a person at precise locations. These ideal patterns are then compared to the real synergy map using a discriminative measure in order to decide whether a person is present or not. This approach is novel because rather than a priori decision rules to remove the ghosts, we propose to compare the physical reality of the scene with the synthetic data, and thus, validate or not the assumptions of people detection using pattern matching methods. The proposed method achieves excellent results on the PETS 2009 dataset as demonstrated by comparison with state-of-the-art methods.
Year
DOI
Venue
2014
10.1145/2659021.2659031
ICDSC
Keywords
Field
DocType
algorithms,multi-view geometry,multi-camera surveillance,shape analysis,object recognition,people localization,vision and scene understanding
Decision rule,Computer vision,Computer science,A priori and a posteriori,Synthetic data,Planar,Artificial intelligence,Discriminative model,Pattern matching,Shape analysis (digital geometry)
Conference
Citations 
PageRank 
References 
0
0.34
12
Authors
3
Name
Order
Citations
PageRank
Muhammad Owais Mehmood161.82
Sebastien Ambellouis2649.91
Catherine Achard300.34