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• W2912592243 abstract "Abstract Many multi-camera applications rely on the knowledge of the spatial relationship among the individual nodes. However, establishing such a network-wide calibration is typically a time-consuming task and requires user interaction. In this paper we present a decentralized and resource-aware algorithm for estimating the poses of all network nodes without any user interaction. This self-calibration of the network is achieved in two steps: First, overlapping camera pairs estimate relative positions and orientations by exchanging locally measured distances and angles to detected objects. Second, calibration information of overlapping cameras is spread throughout the network such that poses of non-overlapping cameras can also be estimated. Our approach does not rely on a priori topological information and delivers the extrinsic camera parameters with respect to a common coordinate system. In a simulation study we analyze the performance of our approach concerning the achieved spatial accuracy and computational effort considering noisy measurements and different communication schemes." @default.
• W2912592243 created "2019-02-21" @default.
• W2912592243 creator A5024032794 @default.
• W2912592243 creator A5059055031 @default.
• W2912592243 date "2019-05-01" @default.
• W2912592243 modified "2023-09-24" @default.
• W2912592243 title "Decentralized and resource-efficient self-calibration of visual sensor networks" @default.
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• W2912592243 doi "https://doi.org/10.1016/j.adhoc.2019.01.007" @default.
• W2912592243 hasPublicationYear "2019" @default.
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