Recovering the Topology of Multiple Cameras by Finding Continuous Paths in a Trellis

In this paper, we propose an unsupervised method for recovering the topology of multiple cameras with non-overlapping fields of view. The nodes in the topology graph are defined as entry/exit zones in each camera while the connectivity between nodes is inferred through finding continuous paths in a...

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Published in2010 20th International Conference on Pattern Recognition pp. 3541 - 3544
Main Authors Yinghao Cai, Kaiqi Huang, Tieniu Tan, Pietikäinen, Matti
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2010
Subjects
Cameras
Color
Image color analysis
Network topology
Nickel
Search problems
Topology
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Abstract In this paper, we propose an unsupervised method for recovering the topology of multiple cameras with non-overlapping fields of view. The nodes in the topology graph are defined as entry/exit zones in each camera while the connectivity between nodes is inferred through finding continuous paths in a trellis where appearance information and temporal information of moving objects are encoded. Unlike previous methods which assume a single mode transition distribution between nodes, our method is capable of dealing with multi-modal transition situations when both cars and pedestrians are in the scene. Results on simulated and real-life datasets demonstrate the effectiveness of the proposed method.
AbstractList In this paper, we propose an unsupervised method for recovering the topology of multiple cameras with non-overlapping fields of view. The nodes in the topology graph are defined as entry/exit zones in each camera while the connectivity between nodes is inferred through finding continuous paths in a trellis where appearance information and temporal information of moving objects are encoded. Unlike previous methods which assume a single mode transition distribution between nodes, our method is capable of dealing with multi-modal transition situations when both cars and pedestrians are in the scene. Results on simulated and real-life datasets demonstrate the effectiveness of the proposed method.
Author Kaiqi Huang
Pietikäinen, Matti
Yinghao Cai
Tieniu Tan
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  surname: Tieniu Tan
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  email: mkp@ee.oulu.fi
  organization: Dept. of Electr. & Inf. Eng., Univ. of Oulu, Oulu, Finland
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Snippet In this paper, we propose an unsupervised method for recovering the topology of multiple cameras with non-overlapping fields of view. The nodes in the topology...
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SubjectTerms Cameras
Color
Image color analysis
Network topology
Nickel
Search problems
Topology
Title Recovering the Topology of Multiple Cameras by Finding Continuous Paths in a Trellis
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