"Feature-based calibration of distributed smart stereo camera networks" by Aaron Mavrinac

Date of Award

2008

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Electrical and Computer Engineering

Keywords

Engineering, Electronics and Electrical.

Supervisor

Chen, Xiang (Electrical & Computer Engineering), Tepe, Kemal (Electrical & Computer Engineering)

Rights

info:eu-repo/semantics/openAccess

Abstract

A distributed smart camera network is a collective of vision-capable devices with enough processing power to execute algorithms for collaborative vision tasks. A true 3D sensing network applies to a broad range of applications, and local stereo vision capabilities at each node offer the potential for a particularly robust implementation. A novel spatial calibration method for such a network is presented, which obtains pose estimates suitable for collaborative 3D vision in a distributed fashion using two stages of registration on robust 3D features. The method is first described in a general, modular sense, assuming some ideal vision and registration algorithms. Then, existing algorithms are selected for a practical implementation. The method is designed independently of networking details, making only a few basic assumptions about the underlying network's capabilities. Experiments using both software simulations and physical devices are designed and executed to demonstrate performance.

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