Large-Scale Camera Network Topology Estimation by Lighting Variation

被引：0

作者：

Zhu, Michael ^{[1
]}

Dick, Anthony ^{[1
]}

van den Hengel, Anton ^{[1
]}

机构：

[1] Univ Adelaide, Australian Ctr Visual Technol, Adelaide, SA 5005, Australia

来源：

ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS (ACIVS 2017) | 2017年 / 10617卷

关键词：

Large-scale intelligent video surveillance; Topology estimation; Light-overlap; Lighting variation detection; Segmentation;

D O I：

10.1007/978-3-319-70353-4_39

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a scalable and robust algorithm to find connections between cameras in a large surveillance network, based solely on lighting variation. We show how to detect regions that are affected by lighting changes within each camera view, with limited data. Then, we establish the light-overlap connections and show that our algorithm can scale to hundreds of camera while maintaining high accuracy. We demonstrate our method on a campus network of 100 real cameras and 500 simulated cameras, and evaluate its accuracy and scalability.

引用

页码：455 / 467

页数：13

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